2
1
United States
1 year of experience
Ladies and gentlemen, allow me to introduce you to the one and only, the trapper-turned-hacker extraordinaire - he's the man, the myth, the legend - he's the Hackman! "Born in the gritty streets of New York City, the Hackman started out as a trapper, hustling and bustling to make ends meet. But, like a phoenix rising from the ashes, he transformed his life and embarked on a journey of ethical hacking and service leadership. He's like a modern-day Robin Hood, stealing from the rich and giving to the poor - only instead of robbing banks, he's hacking into their systems and exposing their dirty secrets. "But the Hackman is more than just a computer whiz - he's a man on a mission. He's here to awaken humanity to the dangers of unethical hacking and to show us the light of ethical hacking. He's a crusader, a hero, a man of the people. "So, let's give it up for the Hackman - the man who went from trapping to hacking, and who's now using his skills to make the world a better place. Let's hear it for the one and only - the Hackman!"
This was a collaboration between two finalists in the Open Interpreter Hackathon. Using mixtral-8x7b-24 the large language model for open-interpreter now allows a user to access a llm that beats chatgpt in certain metrics. For our use case we use huggingface as a provider. Meaning this workflow is free of charge. However, the dataset was vectorized using openai due to time constraints. Similar to the open-interpreter toolkit the user is able to have the agent use scripts as tools. The tool we made is query_documents. How the user is not only able to use the agent to sort books, but now they can be queried. This allows for very interesting workflows. One the the future uses of this is to modify the outputs using agentprotocols. We continued the progress of a former hackathon on LabLab.AI found here. The world's first self-coded, self-categorized, and self-sorted library in the world found here: https://lablab.ai/event/open-interpreter-hackathon/2600-books-files-sorted/2600-books-sorted-for-multi-agent-creation. This time we did mass book summarization of the Education category in order to prepare to create an educational administrator agent to practice sales pitches for an AI literacy curriculum. Enjoy the video. Be well. Here's the link to the leaders' project as well: https://lablab.ai/event/open-interpreter-hackathon/open-interpreter-toolkit/open-interpreter-tool-kit