https://github.com/lmnr-ai/lmnr
Laminar - open-source all-in-one platform for engineering AI products. Crate data flywheel for you AI app. Traces, Evals, Datasets, Labels. YC S24.
https://github.com/lmnr-ai/lmnr
agents ai ai-observability aiops analytics developer-tools evals evaluation llm-evaluation llm-observability llm-workflow llmops monitoring observability open-source pipeline-builder rag rust-lang self-hosted
Last synced: about 2 months ago
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Laminar - open-source all-in-one platform for engineering AI products. Crate data flywheel for you AI app. Traces, Evals, Datasets, Labels. YC S24.
- Host: GitHub
- URL: https://github.com/lmnr-ai/lmnr
- Owner: lmnr-ai
- License: apache-2.0
- Created: 2024-08-29T03:45:28.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2025-04-10T17:38:31.000Z (about 1 year ago)
- Last Synced: 2025-04-10T18:48:07.287Z (about 1 year ago)
- Topics: agents, ai, ai-observability, aiops, analytics, developer-tools, evals, evaluation, llm-evaluation, llm-observability, llm-workflow, llmops, monitoring, observability, open-source, pipeline-builder, rag, rust-lang, self-hosted
- Language: TypeScript
- Homepage: https://www.lmnr.ai
- Size: 28.9 MB
- Stars: 1,793
- Watchers: 11
- Forks: 106
- Open Issues: 18
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
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README
# Laminar
[Laminar](https://laminar.sh) is an open-source observability platform purpose-built for AI agents.
- [x] Tracing. [Docs](https://docs.laminar.sh/tracing/introduction)
- [x] OpenTelemetry-native powerful tracing SDK - 1 line of code to automatically trace **Vercel AI SDK, Browser Use, Stagehand, LangChain, OpenAI, Anthropic, Gemini, and more**.
- [x] Evals. [Docs](https://docs.laminar.sh/evaluations/introduction)
- [x] Unopinionated, extensible SDK and CLI for running evals locally or in CI/CD pipeline.
- [x] UI for visualizing evals and comparing results.
- [x] AI monitoring. [Docs](https://docs.laminar.sh/signals)
- [x] Define events with natural language descriptions to track issues, logical errors, and custom behavior of your agent.
- [x] SQL access to all data. [Docs](https://docs.laminar.sh/platform/sql-editor)
- [x] Query traces, metrics, and events with a built-in SQL editor. Bulk create datasets from queries. Available via API.
- [x] Dashboards. [Docs](https://docs.laminar.sh/custom-dashboards/overview)
- [x] Powerful dashboard builder for traces, metrics, and events with support of custom SQL queries.
- [x] Data annotation & Datasets. [Docs](https://docs.laminar.sh/datasets/introduction)
- [x] Custom data rendering UI for fast data annotation and dataset creation for evals.
- [x] Extremely high performance.
- [x] Written in Rust 🦀
- [x] Custom realtime engine for viewing traces as they happen.
- [x] Ultra-fast full-text search over span data.
- [x] gRPC exporter for tracing data.
## Documentation
Check out full documentation here [docs.laminar.sh](https://docs.laminar.sh).
## Getting started
The fastest and easiest way to get started is with our managed platform -> [laminar.sh](https://laminar.sh)
### Self-hosting with Docker compose
Laminar is very easy to self-host locally. For a quick start, clone the repo and start the services with docker compose:
```sh
git clone https://github.com/lmnr-ai/lmnr
cd lmnr
docker compose up -d
```
This will spin up a lightweight but full-featured version of the stack. This is good for a quickstart
or for lightweight usage. You can access the UI at http://localhost:5667 in your browser.
You will also need to properly configure the SDK, with `baseUrl` and correct ports. See [guide on self-hosting](https://docs.laminar.sh/hosting-options#self-hosted-docker-compose).
For production environment, we recommend using our [managed platform](https://laminar.sh) or `docker compose -f docker-compose-full.yml up -d`.
### Enabling the Signals feature
To enable [Signals / AI monitoring](https://docs.laminar.sh/signals) in self-hosted mode, set the `GOOGLE_GENERATIVE_AI_API_KEY` environment variable in your `.env` file. This key is required by both the app-server and the frontend.
```sh
# In .env at the repo root
GOOGLE_GENERATIVE_AI_API_KEY=your_key_here
```
## Contributing
For running and building Laminar locally, or to learn more about docker compose files,
follow the guide in [Contributing](/CONTRIBUTING.md).
## TS quickstart
First, [create a project](https://laminar.sh/projects) and generate a project API key. Then,
```sh
npm add @lmnr-ai/lmnr
```
It will install Laminar TS SDK and all instrumentation packages (OpenAI, Anthropic, LangChain ...)
To start tracing LLM calls just add
```typescript
import { Laminar } from '@lmnr-ai/lmnr';
Laminar.initialize({ projectApiKey: process.env.LMNR_PROJECT_API_KEY });
```
To trace inputs / outputs of functions use `observe` wrapper.
```typescript
import { OpenAI } from 'openai';
import { observe } from '@lmnr-ai/lmnr';
const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const poemWriter = observe({name: 'poemWriter'}, async (topic) => {
const response = await client.chat.completions.create({
model: "gpt-4o-mini",
messages: [{ role: "user", content: `write a poem about ${topic}` }],
});
return response.choices[0].message.content;
});
await poemWriter();
```
## Python quickstart
First, [create a project](https://laminar.sh/projects) and generate a project API key. Then,
```sh
pip install --upgrade 'lmnr[all]'
```
It will install Laminar Python SDK and all instrumentation packages. See list of all instruments [here](https://docs.laminar.sh/installation)
To start tracing LLM calls just add
```python
from lmnr import Laminar
Laminar.initialize(project_api_key="")
```
To trace inputs / outputs of functions use `@observe()` decorator.
```python
import os
from openai import OpenAI
from lmnr import observe, Laminar
Laminar.initialize(project_api_key="")
client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
@observe() # annotate all functions you want to trace
def poem_writer(topic):
response = client.chat.completions.create(
model="gpt-4o",
messages=[
{"role": "user", "content": f"write a poem about {topic}"},
],
)
poem = response.choices[0].message.content
return poem
if __name__ == "__main__":
print(poem_writer(topic="laminar flow"))
```
## Client libraries
To learn more about instrumenting your code, check out our client libraries:
