🗓️ 48-hour AI Challenge - Build your own AI agent or agent simulation over the weekend
🦜 Power up your coding with the LangChain framework!
🤝 Connect with potential co-founders and mentors at the event

AI Agents Hackathon 2.0

No-rank

Apprentice

eyany

We made an AI Trip Planner that takes in a city a user wants to visit, and create an itinerary with time for some attractions in the city. AITripz gives them some extra information such as weather, cultural tips,  hotel options, and where to eat. We used LangChain to prompt LLM and chat models, and enrich with info from Google Map API. To make this interactive, it is a Streamlit web application.

The goal is to lessen the burden of information gathering, processing, and accumulation so that they could have a lot of these information on hand to customize if necessary, or just follow the itinerary exactly if they wish. 

AITripz

Large language models (LLMs) have transformed the way we approach machine learning and artificial intelligence. These models are incredibly powerful, but their true potential lies in their ability to work in harmony with other sources of data and computation. This library has been developed to assist developers in building applications that combine LLMs with other technologies, allowing them to create truly intelligent and innovative products.

LangChain

Auto-GPT is an experimental open-source application that showcases the capabilities of the GPT-4 language model. This program, driven by GPT-4, chains together LLM 'thoughts' to autonomously achieve whatever goal you set.

Auto-GPT

BabyAGI is a Python project that demonstrates an AI-powered task management system that uses OpenAI and Pinecone APIs to create, prioritize and execute tasks.

BabyAGI

LLaMA (Large Language Model Meta AI) is a state-of-the-art foundational large language model designed to help researchers advance their work in the subfield of AI. It is available in multiple sizes (7B, 13B, 33B, and 65B parameters) and aims to democratize access to large language models by requiring less computing power and resources for training and deployment.

Eyan Yeung@eyany

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🤝 Top Collabolators

Eyan Yeung

🤓 Submissions

AITripz

📝 Certificates

AI Agents Hackathon 2.0 | Certificate