Imagine this: You're working on a project with the assistance of an AI. The AI is helping you write code and providing insights into your data. However, as your project grows larger and more complex, the AI seems to lose track of your progress. You find yourself repeating explanations and providing context to the AI over and over again. It's frustrating and time-consuming, and it slows down your progress.
What if there was a way to easily provide the AI with a snapshot of your entire project in a format that it could understand?
This is where Snapshot for AI comes in. Snapshots for AI is a drag and drop devlops tool that allows you to quickly generate a machine/AI-readable documentation that shows your project's current folder and file structure, as well as the updated contents of all the files, all inside a markdown file.
With the markdown snapshots generated from this tool, developers can easily and quickly provide ChatGPT with the information it needs to keep track of your project, saving you time and increasing productivity.
You can even setup the python script to auto generate the introductionary prompt for every markdown snapshot. This means that you can find tune the expectations you set to the API on how to respond after it reads your application details.
Another powerful feature of Snapshots for AI is its ability to automatically detect and obfuscate sensitive keys in JSON files. This means that your private keys are better protected from unknown observers.
This utility also features a customizable pattern-based ignore system that helps you prevent including unwanted information in your markdown reports. We know we need to keep character counts down when sending the AI information, and with these controls we can reduce the overall package to only the relevant material.
To use Snapshot for AI, you'll need to have Python installed on your machine.
After installing Python, you can install the required dependencies by running the following command in the terminal:
pip install -r requirements.txt
This will install all the required packages listed in the requirements.txt file.
Then to run the script and generate a snapshot, open your terminal and input:
python snapshots.py
And an MD File will be copied to your clipboard and stored in the application's ./snapshots/captures/ folder.
Here's an example of a markdown snapshot generated within a NextJS Hello World project.
https://github.com/gbti-labs/assets/blob/master/snapshots-for-ai/example-snapshot.md
In conclusion, Snapshot for AI is a powerful tool that can help you streamline your workflow and increase productivity when working with an AI.
In the future we imagine AI will be baked directly into the IDE, but for now, we're using this tool to save a lot of time.
If you're interested in learning more about Snapshot for AI or joining the GBTI community, please visit our website or reach out to us on social media.
https://gbti.io/ (Private Collaborative Community for Developers)
Tanstafl join our club!
Top comments (0)