
langtrace
Langtrace π 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. ππ»π
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Langtrace is an open source observability software that lets you capture, debug, and analyze traces and metrics from all your applications that leverage LLM APIs, Vector Databases, and LLM-based Frameworks. It supports Open Telemetry Standards (OTEL), and the traces generated adhere to these standards. Langtrace offers both a managed SaaS version (Langtrace Cloud) and a self-hosted option. The SDKs for both Typescript/Javascript and Python are available, making it easy to integrate Langtrace into your applications. Langtrace automatically captures traces from various vendors, including OpenAI, Anthropic, Azure OpenAI, Langchain, LlamaIndex, Pinecone, and ChromaDB.
README:
- β¨ Features
- π Quick Start
- π Integrations
- π Getting Started
- π Self Hosting
- π Architecture
- π€ Contributing
- π Security
- β FAQ
- π₯ Contributors
- π 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.
- π Open Telemetry Support: Built on OTEL standards for comprehensive tracing
- π Real-time Monitoring: Track LLM API calls, vector operations, and framework usage
- π― Performance Insights: Analyze latency, costs, and usage patterns
- π Debug Tools: Trace and debug your LLM application workflows
- π Analytics: Get detailed metrics and visualizations
- π Self-hosting Option: Deploy on your own infrastructure
# 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.
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.
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:
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
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
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
Feel free to modify the .env
file to suit your needs.
docker compose up
The application will be available at http://localhost:3000
.
To delete containers and volumes
docker compose down -v
-v
flag is used to delete volumes
Langtrace does NOT collect any Telemetry if you are self hosting the OSS client. None of your data leaves your servers.
Langtrace automatically captures traces from the following vendors and frameworks:
Provider | TypeScript SDK | Python SDK |
---|---|---|
OpenAI | β | β |
Anthropic | β | β |
Azure OpenAI | β | β |
Cohere | β | β |
DeepSeek | β | β |
xAI | β | β |
Groq | β | β |
Perplexity | β | β |
Gemini | β | β |
AWS Bedrock | β | β |
Mistral | β | β |
Framework | TypeScript SDK | Python SDK |
---|---|---|
Langchain | β | β |
LlamaIndex | β | β |
Langgraph | β | β |
LiteLLM | β | β |
DSPy | β | β |
CrewAI | β | β |
Ollama | β | β |
VertexAI | β | β |
Vercel AI | β | β |
GuardrailsAI | β | β |
Arch | β | β |
Graphlit | β | β |
Agno | β | β |
Phidata | β | β |
Cleanlab | β | β |
Database | TypeScript SDK | Python SDK |
---|---|---|
Pinecone | β | β |
ChromaDB | β | β |
QDrant | β | β |
Weaviate | β | β |
PGVector | β | β (SQLAlchemy) |
MongoDB | β | β |
Milvus | β | β |
- To request for features, head over here to start a discussion.
- To raise an issue, head over here and create an issue.
We welcome contributions to this project. To get started, fork this repository and start developing. To get involved, join our Slack workspace.
To report security vulnerabilities, email us at [email protected]. You can read more on security here.
- 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.
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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.
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