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https://github.com/openlit/helm
Helm Charts to deploy and manage OpenLIT in Kubernetes
https://github.com/openlit/helm
aiops claude clickhouse docker gpt helm helm-charts kubernetes llm llmops mistral-7b monitor monitoring monitoring-tool observability openai
Last synced: 9 days ago
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Helm Charts to deploy and manage OpenLIT in Kubernetes
- Host: GitHub
- URL: https://github.com/openlit/helm
- Owner: openlit
- License: apache-2.0
- Created: 2024-03-27T08:14:04.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-10-26T18:15:59.000Z (25 days ago)
- Last Synced: 2024-10-26T20:14:25.684Z (25 days ago)
- Topics: aiops, claude, clickhouse, docker, gpt, helm, helm-charts, kubernetes, llm, llmops, mistral-7b, monitor, monitoring, monitoring-tool, observability, openai
- Language: Smarty
- Homepage:
- Size: 120 KB
- Stars: 3
- Watchers: 1
- Forks: 3
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Codeowners: CODEOWNERS
- Security: SECURITY.md
Awesome Lists containing this project
README
OpenTelemetry-native LLM Application Observability
**[Documentation](https://docs.openlit.io/) | [Quickstart](#-getting-started) | [Python SDK](https://github.com/openlit/openlit/tree/main/sdk/python)**
[](https://github.com/openlit/openlit)
[](https://github.com/openlit/helm/blob/main/LICENSE)
[](https://pepy.tech/project/openlit)
[](https://github.com/openlit/helm/pulse)
[](https://github.com/openlit/helm/graphs/contributors)
[](https://github.com/openlit/helm/tags)
[](https://github.com/openlit/helm/actions/workflows/helm-test.yml)
[](https://join.slack.com/t/openlit/shared_invite/zt-2etnfttwg-TjP_7BZXfYg84oAukY8QRQ)
[](https://twitter.com/openlit_io)
## Introduction
OpenLIT is an **OpenTelemetry-native** GenAI and LLM Application Observability tool. It's designed to make the integration process of observability into GenAI projects as easy as pie – literally, with just **a single line of code**. Whether you're working with popular LLM Libraries such as OpenAI and HuggingFace or leveraging vector databases like ChromaDB, OpenLIT ensures your applications are monitored seamlessly, providing critical insights to improve performance and reliability.
This project proudly follows the [Semantic Conventions](https://github.com/open-telemetry/semantic-conventions/tree/main/docs/gen-ai) of the OpenTelemetry community, consistently updating to align with the latest standards in observability.
## 💿 Installation
To install the OpenLIT chart with the release name `openlit`:
```bash
helm repo add openlit https://openlit.github.io/helm/
helm repo update
helm install openlit openlit/openlit
```
> 🔧 **Note:** If the `openlit` StatefulSet Pod appears in an error state after installing the OpenLIT Helm chart, it may be due to the ClickHouse setup. Allow time for ClickHouse to fully initialize, which should help the `openlit` pod become healthy. If issues persist, restarting the `openlit` pod will resolve the issue.
## 🚀 Getting Started post Installation
After the OpenLIT chart is successfully deployed to your Kubernetes cluster, you'll need to generate an API key that can be used by the OpenLITmetry SDKs to authenticate requests to the OpenLIT platform.
### ⚡️ Instrument your Application with OpenLIT
Select the SDK that matches your application's programming language and integrate LLM monitoring with just a **single line of code**.
Install the `openlit` [Python SDK](https://pypi.org/project/openlit/) using pip:
```shell
pip install openlit
```
Add the following two lines to your application code:
```python
import openlit
openlit.init()
```
##### Example Usage for monitoring `OpenAI` Usage:
```python
from openai import OpenAI
import openlit
openlit.init()
client = OpenAI(
api_key="YOUR_OPENAI_KEY"
)
chat_completion = client.chat.completions.create(
messages=[
{
"role": "user",
"content": "What is LLM Observability",
}
],
model="gpt-3.5-turbo",
)
```
Refer to the `openlit` [Python SDK repository](https://github.com/openlit/openlit/tree/main/sdk/python) for more advanced configurations and use cases.
### Visualize and Analyze
Once you have `OpenLIT` SDKs set up, you can instantly get insights into how your LLM applications. Just head over to OpenLIT UI at `127.0.0.1:3000` on your browser to start exploring.
With OpenLIT, you get a simple, powerful view into important info like how much you’re spending on LLMs, which parts of your app are using them the most, and how well they’re performing. Find out which LLM models are favorites among your applications, and dive deep into performance details to make smart decisions. This setup is perfect for optimizing your app performance and keeping an eye on costs.
### Configuring OpenLIT
You can adjust the OpenLIT configuration by specifying each parameter using the `--set key=value` argument to `helm install`. For example:
```bash
helm install openlit \
--set openlit.service.type=NodePort \
--set openlit.service.port=3000 \
openlit/openlit
```
Alternatively, you can provide a YAML file that specifies the values for the required parameters while installing the chart. For example:
```bash
helm install openlit -f values.yaml openlit/openlit
```
## Upgrading the Chart
To upgrade the `openlit` deployment:
```bash
helm upgrade openlit openlit/openlit
```
## Uninstalling the Chart
To uninstall/delete the `openlit` deployment:
```bash
helm delete openlit
```
If you've made any changes to [`values.yaml`](values.yaml), remember to use the `-f` flag to provide the updated file.
## Contributing
We welcome contributions to the OpenLIT project. Please refer to [CONTRIBUTING](../../CONTRIBUTING) for detailed guidelines on how you can participate.
## License
OpenLIT is available under the [Apache-2.0 license](../../LICENSE).
## Support
For support, issues, or feature requests, submit an issue through the GitHub issues associated with the OpenLIT Repository and add `Helm` label.