fvisconti

Your task is to "onboard" this repository to Copilot coding agent by adding a .github/copilot-instructions.md file in the repository that contains information describing how a coding agent seeing it for the first time can work most efficiently.

You will do this task only one time per repository and doing a good job can SIGNIFICANTLY improve the quality of the agent's work, so take your time, think carefully, and search thoroughly before writing the instructions.

<Goals>
- Reduce the likelihood of a coding agent pull request getting rejected by the user due to
generating code that fails the continuous integration build, fails a validation pipeline, or
having misbehavior.
- Minimize bash command and build failures.
- Allow the agent to complete its task more quickly by minimizing the need for exploration using grep, find, str_replace_editor, and code search tools.

fvisconti

# Since procedures to install TensorRT-LLM such as
# here: https://nvidia.github.io/TensorRT-LLM/installation/linux.html
# or here: https://developer.nvidia.com/blog/optimizing-inference-on-llms-with-tensorrt-llm-now-publicly-available/
# suffer more than an issue, 
# I share my Dockerfile to have it built as a docker image locally

# First stage for building dependencies with a slim Python base
FROM python:3.10-slim-bullseye AS build-deps

RUN apt-get update && apt-get install -y --no-install-recommends \