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50 lines
2.1 KiB
Markdown
50 lines
2.1 KiB
Markdown
# GPT4All Monitoring
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GPT4All integrates with [OpenLIT](https://github.com/openlit/openlit) OpenTelemetry auto-instrumentation to perform real-time monitoring of your LLM application and GPU hardware.
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Monitoring can enhance your GPT4All deployment with auto-generated traces and metrics for
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- **Performance Optimization:** Analyze latency, cost and token usage to ensure your LLM application runs efficiently, identifying and resolving performance bottlenecks swiftly.
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- **User Interaction Insights:** Capture each prompt and response to understand user behavior and usage patterns better, improving user experience and engagement.
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- **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.
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## Setup Monitoring
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!!! note "Setup Monitoring"
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With [OpenLIT](https://github.com/openlit/openlit), you can automatically monitor traces and metrics for your LLM deployment:
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```shell
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pip install openlit
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```
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```python
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from gpt4all import GPT4All
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import openlit
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openlit.init() # start
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# openlit.init(collect_gpu_stats=True) # Optional: To configure GPU monitoring
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model = GPT4All(model_name='orca-mini-3b-gguf2-q4_0.gguf')
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# Start a chat session and send queries
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with model.chat_session():
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response1 = model.generate(prompt='hello', temp=0)
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response2 = model.generate(prompt='write me a short poem', temp=0)
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response3 = model.generate(prompt='thank you', temp=0)
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print(model.current_chat_session)
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```
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## Visualization
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### OpenLIT UI
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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.
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### Grafana, DataDog, & Other Integrations
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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).
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