> * Fabric now supports calling the new `o1-preview` model using the `-r` switch (which stands for raw. Normal queries won't work with `o1-preview` because they disabled System access and don't allow us to set `Temperature`.
> * We have early support for Raycast! Under the `/patterns` directory there's a `raycast` directory with scripts that can be called from Raycast. If you add a scripts directory within Raycast and point it to your `~/.config/fabric/patterns/raycast` directory, you'll then be able to 1) invoke Raycast, type the name of the script, and then 2) paste in the content to be passed, and the results will return in Raycast. There's currently only one script in there but I am (Daniel) adding more.
Keep in mind that many of these were recorded when Fabric was Python-based, so remember to use the current [install instructions](#Installation) below.
Since the start of 2023 and GenAI we've seen a massive number of AI applications for accomplishing tasks. It's powerful, but _it's not easy to integrate this functionality into our lives._
<divalign="center">
<h4>In other words, AI doesn't have a capabilities problem—it has an <em>integration</em> problem.</h4>
</div>
Fabric was created to address this by enabling everyone to granularly apply AI to everyday challenges.
## Philosophy
> AI isn't a thing; it's a _magnifier_ of a thing. And that thing is **human creativity**.
We believe the purpose of technology is to help humans flourish, so when we talk about AI we start with the **human** problems we want to solve.
### Breaking problems into components
Our approach is to break problems into individual pieces (see below) and then apply AI to them one at a time. See below for some examples.
Prompts are good for this, but the biggest challenge I faced in 2023——which still exists today—is **the sheer number of AI prompts out there**. We all have prompts that are useful, but it's hard to discover new ones, know if they are good or not, _and manage different versions of the ones we like_.
One of <code>fabric</code>'s primary features is helping people collect and integrate prompts, which we call _Patterns_, into various parts of their lives.
Fabric has Patterns for all sorts of life and work activities, including:
You may need to set some environment variables in your `~/.bashrc` on linux or `~/.zshrc` file on mac to be able to run the `fabric` command. Here is an example of what you can add:
If you have the Legacy (Python) version installed and want to migrate to the Go version, here's how you do it. It's basically two steps: 1) uninstall the Python version, and 2) install the Go version.
```bash
# Uninstall Legacy Fabric
pipx uninstall fabric
# Clear any old Fabric aliases
(check your .bashrc, .zshrc, etc.)
# Install the Go version
go install github.com/danielmiessler/fabric@latest
# Run setup for the new version. Important because things have changed
The great thing about Go is that it's super easy to upgrade. Just run the same command you used to install it in the first place and you'll always get the latest version.
```bash
go install github.com/danielmiessler/fabric@latest
-r, --raw Use the defaults of the model without sending chat options (like temperature etc.) and use the user role instead of the system role for patterns
- **First, we use `Markdown` to help ensure maximum readability and editability**. This not only helps the creator make a good one, but also anyone who wants to deeply understand what it does. _Importantly, this also includes the AI you're sending it to!_
- **And finally, we tend to use the System section of the prompt almost exclusively**. In over a year of being heads-down with this stuff, we've just seen more efficacy from doing that. If that changes, or we're shown data that says otherwise, we will adjust.
3. Run the `extract_wisdom` Pattern with the `--stream` option to get immediate and streaming results from any Youtube video (much like in the original introduction video).
If you're not looking to do anything fancy, and you just want a lot of great prompts, you can navigate to the [`/patterns`](https://github.com/danielmiessler/fabric/tree/main/patterns) directory and start exploring!
We hope that if you used nothing else from Fabric, the Patterns by themselves will make the project useful.
You can use any of the Patterns you see there in any AI application that you have, whether that's ChatGPT or some other app or website. Our plan and prediction is that people will soon be sharing many more than those we've published, and they will be way better than ours.
You may want to use Fabric to create your own custom Patterns—but not share them with others. No problem!
Just make a directory in `~/.config/custompatterns/` (or wherever) and put your `.md` files in there.
When you're ready to use them, copy them into:
```
~/.config/fabric/patterns/
```
You can then use them like any other Patterns, but they won't be public unless you explicitly submit them as Pull Requests to the Fabric project. So don't worry—they're private to you.
This will create a PDF file named `output.pdf` in the current directory.
### `to_pdf` Installation
To install `to_pdf`, install it the same way as you install Fabric, just with a different repo name.
```bash
go install github.com/danielmiessler/fabric/to_pdf/to_pdf@latest
```
Make sure you have a LaTeX distribution (like TeX Live or MiKTeX) installed on your system, as `to_pdf` requires `pdflatex` to be available in your system's PATH.
- _Jonathan Dunn_ for being the absolute MVP dev on the project, including spearheading the new Go version, as well as the GUI! All this while also being a full-time medical doctor!
- _Jason Haddix_ for the idea of a stitch (chained Pattern) to filter content using a local model before sending on to a cloud model, i.e., cleaning customer data using `llama2` before sending on to `gpt-4` for analysis.
