GPT Computer Assistant(GCA) | 5K Star

Hi folks, I'm Bartu, One of the co-founders of the GPT Computer Assistant (GCA). At OpenAI's GPT-4 launch in May, they said the future of their assistants was on new computers, and we wanted to democratize it. We designed the GPT computer assistant framework to support Windows, Linux, and MacOS.🧑‍💻 Why we say Intelligence, not Assistant - The Tool capability of the intelligence you will create with GCA is very high - Agentic infrastructure is available - You can add custom tools and create ordered tasks - We call it 'intelligence' because it can also be used as a framework. Assistants are usually tools that use the assistant capabilities of GPT-4 with an interface. When you allocate enough development time (700+ hours), you can reach GCA's level but we already offer it for free in a form that includes many APIs that you can easily customize. 🧩 We support both cloud and many local models. We believe that open-source models are critical for the democratization of AI. 👉 How to build intelligence for your product with the GPT Computer Assistant - A wide range of APIs are available for many things such as logo, product name, characterization - You can customize the agent infrastructure according to your product, so you can get higher quality AI outputs - By adding custom tools for agent infrastructure, you will get accurate results in specific tasks Experience✨ - It answers your question in less than a second in local models. - To get out of the monotony, we voice the answers the assistant gives in three different voices. - It understands when your conversation is over and acts according to your commands. - You can silence GCA without finishing its speech - You can see the path it followed to respond to your commands.

Congrats on the launch! where do you see CGA having the most common use cases? Explain it to me like if I wasn't a Dev ('cause I'm not ahah)

This is so smart! Great addition to any AI infrastructure. Congrats on the launch

This looks intriguing, Bartu! I'm curious about how the GCA framework handles integration with existing systems. Is it straightforward to implement for developers who may not be deeply entrenched in AI or machine learning? Also, you mentioned that building with GCA can lead to high-quality outputs—what kind of metrics are you using to measure that? Any real-world examples or case studies of businesses benefiting from this? I’m especially interested in the flexibility of the agentic infrastructure you’ve offered. What kinds of custom tools have other makers found particularly useful? Looking forward to learning more!

Congrats,What level of technical expertise is required to effectively utilize GCA?

A few things that caught my eyes: it's open source, how raw the product interface is (this means you really focused on building this as a framework), the APIs are quite comprehensive, the local LLM support, and the omni experience. Often times though, the use cases are fairly nuanced, so a lot of customization has to be done to make it work. How much time would it take to fine tune the app? Congrats on the launch @bartu and team!

Hey Mehmet, How long does it typically take for someone to set up and start using GCA effectively? Could you give an example of a unique custom tool that can be added to the agent infrastructure? Congrats on the launch!