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# GPT4All Monitoring # GPT4All Monitoring
GPT4All integrates with [OpenLIT](https://github.com/openlit/openlit) open telemetry instrumentation to perform real-time monitoring of your LLM application and hardware. GPT4All integrates with [OpenLIT](https://github.com/openlit/openlit) OpenTelemetry auto-instrumentation to perform real-time monitoring of your LLM application and GPU hardware.
Monitoring can enhance your GPT4All deployment with auto-generated traces for Monitoring can enhance your GPT4All deployment with auto-generated traces and metrics for
- performance metrics - **Performance Optimization:** Analyze latency, cost and token usage to ensure your LLM application runs efficiently, identifying and resolving performance bottlenecks swiftly.
- user interactions - **User Interaction Insights:** Capture each prompt and response to understand user behavior and usage patterns better, improving user experience and engagement.
- GPU metrics like utilization, memory, temperature, power usage - **Detailed GPU Metrics:** Monitor essential GPU parameters such as utilization, memory consumption, temperature, and power usage to maintain optimal hardware performance and avert potential issues.
## Setup Monitoring ## Setup Monitoring
!!! note "Setup Monitoring" !!! note "Setup Monitoring"
With [OpenLIT](https://github.com/openlit/openlit), you can automatically monitor metrics for your LLM deployment: With [OpenLIT](https://github.com/openlit/openlit), you can automatically monitor traces and metrics for your LLM deployment:
```shell ```shell
pip install openlit pip install openlit
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import openlit import openlit
openlit.init() # start openlit.init() # start
# openlit.init(collect_gpu_stats=True) # or, start with optional GPU monitoring # openlit.init(collect_gpu_stats=True) # Optional: To configure GPU monitoring
model = GPT4All(model_name='orca-mini-3b-gguf2-q4_0.gguf') model = GPT4All(model_name='orca-mini-3b-gguf2-q4_0.gguf')
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print(model.current_chat_session) print(model.current_chat_session)
``` ```
## OpenLIT UI ## Visualization
Connect to OpenLIT's UI to start exploring performance metrics. Visit the OpenLIT [Quickstart Guide](https://docs.openlit.io/latest/quickstart) for step-by-step details. ### OpenLIT UI
## Grafana, DataDog, & Other Integrations Connect to OpenLIT's UI to start exploring the collected LLM performance metrics and traces. Visit the OpenLIT [Quickstart Guide](https://docs.openlit.io/latest/quickstart) for step-by-step details.
If you use tools like , you can integrate the data collected by OpenLIT. For instructions on setting up these connections, check the OpenLIT [Connections Guide](https://docs.openlit.io/latest/connections/intro). ### Grafana, DataDog, & Other Integrations
You can also send the data collected by OpenLIT to popular monitoring tools like Grafana and DataDog. For detailed instructions on setting up these connections, please refer to the OpenLIT [Connections Guide](https://docs.openlit.io/latest/connections/intro).