joe, to ai

Earlier this year, I started looking at how to run a fully on-prem AI. In February, I bought a machine to run the inference engine on and set up Tailscale (which works similarly to Hamachi) to connect to it remotely. If you want to use it remotely, there are a lot of options for native clients.

MacOS

My favorite client for MacOS is MindMac. You can buy it for under $30, it works with multiple models, servers, and server types, and it is easy to use.

https://i0.wp.com/jws.news/wp-content/uploads/2024/04/Screenshot-2024-04-20-at-2.34.12%E2%80%AFPM.png?resize=1024%2C690&ssl=1

If you want to look further into it, you can check it out at mindmac.app.

Android

My favorite client for Android is Amallo. It is $23 and like MindMac, it works with multiple models, servers, and server types. My only complaint would be that uploading a base64-encoded image to the model doesn’t seem to work well.

https://i0.wp.com/jws.news/wp-content/uploads/2024/04/Screenshot_20240420-143906.png?resize=461%2C1024&ssl=1

If you want to look further into it, you can check it out at doppeltilde.com.

ipadOS

There is a version of Amallo for iPadOS but I have been liking Enchanted LLM more. If you like it, there is a version for macOS as well. It has the added benefit of being free.

https://i0.wp.com/jws.news/wp-content/uploads/2024/04/IMG_0088.jpg?resize=672%2C1024&ssl=1

If you want to look further into it, you can check it out at the project’s GitHub page.

Have any questions, comments, etc? Please feel free to drop a comment, below.

https://jws.news/2024/how-i-use-ai/

joe, (edited ) to programming

Yesterday, we played with Llama 3 using the Ollama CLI client (or REPL). Today I figured that we would play with it using the Ollama API. The Ollama API is documented on their Github repo. Ollama has a client that runs when you run ollama run llama3 and a service that can be accessed from something like MindMac, Amallo, or Enchanted. The service is what starts when you run ollama serve.

In our first Llama 3 post, we asked the model for “a comma-delimited list of cities in Wisconsin with a population over 100,000 people”. Using Postman and the completion API endpoint, you can ask the same thing.

https://i0.wp.com/jws.news/wp-content/uploads/2024/04/Screenshot-2024-04-20-at-1.30.48%E2%80%AFPM.png?resize=1024%2C811&ssl=1

You will notice the stream parameter is set to false in the body. If the value is false, the response will be returned as a single response object, rather than a stream of objects. If you are using the API with a web application, you will want to ask the model for the answer as JSON and you will probably want to provide an example of how you want the answer formatted.

https://i0.wp.com/jws.news/wp-content/uploads/2024/04/Screenshot-2024-04-20-at-1.45.15%E2%80%AFPM.png?resize=1024%2C811&ssl=1

You can use Node and Node-fetch to do the same thing.

If you run it from the terminal, it will look like this:

https://i0.wp.com/jws.news/wp-content/uploads/2024/04/Screenshot-2024-04-20-at-2.01.19%E2%80%AFPM.png?resize=1024%2C932&ssl=1

Have any questions, comments, etc? Please feel free to drop a comment, below.

https://jws.news/2024/lets-play-more-with-llama-3/

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