Connect a local LLM machine to private LAN applications without exposing the inference endpoint publicly
You should be able to demonstrate the result described in the lesson and explain why each step was necessary.
Step-by-step
Choose the inference machine
Size the model around available VRAM and system RAM.
Run the model service
Use LM Studio or another local runtime and verify local inference first.
Keep the API private
Bind to localhost or the trusted LAN and block Internet access.
Call it from server-side code
Have PHP or Python call the LAN endpoint so browsers never need direct access.
Validate model output
Treat the model response as untrusted data and parse/escape it carefully.
Measure performance
Track latency, token throughput, memory use, and failure rate.
You should be able to demonstrate the result described in the lesson and explain why each step was necessary.
Troubleshooting
If a command or screen differs from the lesson, stop and verify the version you are using before forcing a change.
What you learned
You now understand the purpose of this part of the system and have a concrete result you can verify before continuing to the next lesson.