Open Interpreter Secrets Revealed: Setup Guide & Examples + O1 Light

🚀 How to setup and use Open Interpreter with 3 examples and the problems you might encounter 🚀

Join AppyDave on a deep dive into the groundbreaking AI operating system, Open Interpreter, and its companion app, O1 Lite. Discover how these technologies are revolutionizing computer control with voice commands, making your interaction with technology more seamless and intuitive than ever before.

What's Inside:

- Dive into what Open Interpreter is and how it's changing the game.
- Step-by-step guide on installing Open Interpreter for optimal performance.
- Real-world application: Navigating folders using voice commands.
- Taking control of web applications effortlessly.
- Introduction to O1 Light: A cost-effective solution for voice control.
- How to easily change desktop preferences using Open Interpreter.
- Leveraging O1 Light for advanced voice control functionalities.
- Resources, repositories, and where to find more information.
- Personal insights and honest opinion on Open Interpreter's capabilities and limitations.
- A sneak peek into GPT Academy for those eager to learn more.

Whether you're a developer, tech enthusiast, or just curious about the latest in AI and voice control technology, this video offers valuable insights and practical examples to help you understand and utilize Open Interpreter and O1 Lite.

Key Highlights:

Discover the potential and challenges of controlling your computer through voice commands.
Learn how to set up and troubleshoot Open Interpreter for your use.
Explore practical examples, from navigating directories to modifying system preferences, and understand the system's limitations.
Find out how O1 Lite enhances the voice control experience.
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Chapters:

00:35 - What does Open Interpreter do?
01:47 - How to install Open Interpreter
03:06 - Find Folders on my computer - Example 1
05:52 - Control Web Application - Test 2
08:27 - O1 Light (How much does it cost?)
08:53 - Change Desktop Preferences - Example 3
10:15 - O1 Light Voice Control
10:35 - Repos & More Information
10:50 - My opinion on Open Interpreter
11:34 - GPT Academy

#AppyDave #openinterpreter #voicecontrol #ai #techtutorial #aioperatingsystem

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[zazerb]

Hey mate, thanks a ton for the video. Was exactly what I was looking for, a succinct run through of realistic use cases.

[qiujin]

thanks for testing this out for us Dave! very inspiring

[Mephmt]

I'd be interested in seeing how you integrated Siri with OI. I'm using Android and Windows machines and I have the inference, STT, and TTS all set up, but I haven't gotten the transcribed text into open-interpreter itself from the client phone. I'd love to know how you managed that using Siri.

[xspydazx]

It's actually using Jupiter notebook ...
In the back ground to execute app it is running a cell in notebook, or executing it's code in a cell in Jupiter as it uses the Jupiter client library ....

So to create your own function calling script, you can use instructor (to create the correct json function calling to Jupiter client ) .. IE the template to follow for the call .. as well as your script needs to contain the instructions to follow,
IE to return the code in segments etc, to resolve problems returned . On the next turn, as well as examining the problem and solving first before resubmitting the task, .. as well as asking it to create any function it needs to perform a task, given these progrsmming langs, and gathering info about the os, so that bash can be used where possible, on knowing the system structure, as it should default to scripting first . Until it has learned enough to use the bash . As well as confirming all tasks until the task is fully error free. Enabling for tasks to be auto run ....

The prompt used is quite in-depth ..
Perhaps even to create the "summarizer response* always ... IE collect all past messages and summarize, then use this context to respond, hence the context history should be summarised every as well as calculated as when it goes out of the sliding window context it will need to be concatenated and summarised . As well as stacked if necessary in the past history ... To enable rezumarizing even further back in the history .. giving the model a high briefing of the past. IE optimizing the history shuffling the important context to the front messages and relating the irrelevant ...

Once you have the prompt set all you need to do is intercept the messaging completions and query's and return the responses . Etc . Verbose no verbose (it stores anyways in json message formates so it's easy to update the model during training with these messages ... So you can discuss information with the model first with truth fil and factual data and it will be stored in it's conversations ....then when you upload these and the relevanr document data. In training .. you will have truly taught the model new knowledge as well as had good discussion which it can refer too also ! .,

[ps]

If u use it with gpt 4, it will bankrupt you!! But open source llm alternatives are pretty useless.