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* new skeleton Signed-off-by: Max Cembalest <max@nomic.ai> * v3 docs Signed-off-by: Max Cembalest <max@nomic.ai> --------- Signed-off-by: Max Cembalest <max@nomic.ai>
48 lines
1.6 KiB
Markdown
48 lines
1.6 KiB
Markdown
# GPT4All Monitoring
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GPT4All integrates with [OpenLIT](https://github.com/openlit/openlit) open telemetry instrumentation to perform real-time monitoring of your LLM application and hardware.
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Monitoring can enhance your GPT4All deployment with auto-generated traces for
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- performance metrics
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- user interactions
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- GPU metrics like utilization, memory, temperature, power usage
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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 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) # or, start with optional 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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## OpenLIT UI
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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.
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## Grafana, DataDog, & Other Integrations
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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).
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