Conversation
Summary of ChangesHello @IshDeshpa, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request aims to enhance the user experience by significantly improving the project's documentation. It streamlines the setup process and provides clear, detailed instructions on how to use the main model script, making it much easier for new contributors or users to get started and understand the available functionalities. Highlights
🧠 New Feature in Public Preview: You can now enable Memory to help Gemini Code Assist learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. Click here to enable Memory in your admin console. Using Gemini Code AssistThe full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips. Invoking Gemini You can request assistance from Gemini at any point by creating a comment using either
Customization To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a Limitations & Feedback Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here. You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension. Footnotes
|
There was a problem hiding this comment.
Code Review
This pull request significantly improves the README.md by clarifying the setup instructions and adding a usage section. The renaming of run-model.sh to run-model is also a good change, making the script invocation cleaner. I've provided a couple of suggestions to make the README even more helpful for new users, focusing on adding prerequisites and a concrete usage example to improve the onboarding experience.
| ## Setup | ||
| We use `uv` as our package manager, so whatever OS you are running, install `uv` [as according to the documentation](https://docs.astral.sh/uv/getting-started/installation/). Then, in the repo directory, run `uv sync` to sync the dependencies in the virtual environment. |
There was a problem hiding this comment.
The new "Setup" section is much clearer. To make it even more user-friendly, I suggest a couple of additions:
- Python Prerequisite: Mention that Python 3.13+ is required, as specified in
pyproject.toml. - Executable Permissions: Add a step to make the
run-modelscript executable usingchmod +x run-model.
Here's a possible revision that incorporates these points and uses a numbered list for clarity:
## Setup
This project requires Python 3.13 or newer.
1. Install `uv` [as according to the documentation](https://docs.astral.sh/uv/getting-started/installation/).
2. In the repo directory, run `uv sync` to install dependencies.
3. Make the run script executable:
```bash
chmod +x run-model| ## Usage | ||
| ``` | ||
| ./run-model | ||
| options: | ||
| -h, --help show this help message and exit | ||
| --log LOG [LOG ...] List of parameter names to log each timestep | ||
| (default: velocity, total_energy, array_power) | ||
| --csv CSV Output CSV filename (default: log.csv) | ||
| --graph [GRAPH ...] List of parameter names to graph over time (default: | ||
| graphs all logged parameters) | ||
| --graph-output GRAPH_OUTPUT | ||
| Output directory for graphs (default: output/) | ||
| ``` |
There was a problem hiding this comment.
Displaying the help output in the "Usage" section is very helpful. To further improve it, I recommend adding a concrete usage example. This would show users how to combine different flags to run a simulation with specific parameters.
For instance, you could add an "Example" subsection like this:
### Example
Run the simulation, log velocity and total energy, save it to `custom_log.csv`, and generate a graph for velocity:
```bash
./run-model --log velocity total_energy --graph velocity --csv custom_log.csv
will accept any suggestions for making readme better