It is always hard to find the next home, especially when you move to a new city that you are unfamiliar with. Our project will use Autogen to help you find the right house/apt in a few sentences! And we also help you find logistics such as flight tickets/moving company to a new city!
Our project leverages the Autogen and AgentOps framework to streamline the home-finding and moving process by providing users with tailored options for housing, airline tickets, and moving companies in just a few sentences. Designed to assist those relocating, especially low-income individuals or families, the platform simplifies complex logistics. It monetizes through Cost-Per-Click for listings and Cost-Per-Acquisition for completed bookings, while offering advertising opportunities. By alleviating the burden of searching for affordable, safe housing, the system helps users focus on packing and settling in.

AI Agents Hack with LabLab and MindsDB

Autogen and AgentOps framework that shows you options for housing, airline tickets, and moving companies in just a few sentences!

Autonomous Challenger

AutoGen is an open-source framework by Microsoft that simplifies creating multi-agent systems powered by LLMs. It enables developers to build conversational AI agents that interact with each other, humans, and tools seamlessly.

AutoGen

AgentOps is a platform for monitoring, debugging, and optimizing AI agents in development and production. It offers session replays, metrics dashboards, and custom reporting to track performance, costs, and interactions.

AgentOps

Llama 3.1 is an open-source, state-of-the-art large language model (LLM) by Meta AI. It’s optimized for advanced NLP tasks, offering various model sizes, and focuses on transparency, safety, and accessibility.

Llama 3.1

Meta is a US technology company that owns the social networks Facebook and Instagram, the instant messaging apps WhatsApp and Messenger, and the virtual reality device brand Meta Quest.

Together AI

HouseDNA for Fast Move

TrendScribe is an innovative AI-driven content generation platform that harnesses the power of real-time conversations on Reddit to create engaging, personalized articles for users. By leveraging a sophisticated system of AI agents, TrendScribe automates the entire content creation process, from data collection and analysis to writing and editing.

Users begin by specifying their topics of interest and keywords, allowing TrendScribe to tailor its content discovery process. The platform's AI agents then scour Reddit for the most relevant and trending discussions, analyzing sentiment, extracting key insights, and generating well-crafted articles. These articles are delivered to users based on their subscription plan, providing a steady stream of fresh, pertinent content.

What sets TrendScribe apart is its ability to tap into the collective knowledge and current discussions on Reddit, ensuring that the generated content is not only informative but also timely and relevant to ongoing conversations. The platform's use of advanced natural language processing and machine learning techniques enables it to produce high-quality articles that capture the essence of trending topics.

TrendScribe offers a user-friendly interface where subscribers can review, edit, and publish or download their AI-generated articles. This feature allows for a perfect blend of automated content creation and human refinement, ensuring that the final output aligns with the user's voice and standards.

Ideal for content marketers, bloggers, and businesses looking to maintain an active online presence, TrendScribe significantly reduces the time and effort required for content creation. By automating the research and initial writing process, it allows users to focus on adding their unique perspectives and insights to the generated content.


TrendScribe uses AI to analyze Reddit trends, generating personalized articles for users based on their interests. It streamlines content creation by automating research, writing, and editing, delivering fresh, relevant content to your inbox.

NingNang AI

Generative Agents are computational software that simulate human behavior in interactive applications.

Generative Agents

TrendScribe-Content Generation from Reddit Trends

Introduction
In an era where infectious diseases can rapidly escalate into global pandemics, the ability to make swift, data-driven policy decisions is more critical than ever. We present a groundbreaking multi-agent epidemic simulation tool designed to empower policymakers with actionable insights, enabling them to navigate the complexities of epidemic management effectively.

The Problem
Policymakers face significant challenges during epidemics:

Complex Dynamics: Epidemics involve intricate interactions among individuals, communities, and policies, making outcomes difficult to predict.
Uncertain Outcomes: Without robust predictive tools, policies may lead to unintended consequences, exacerbating the crisis.
Data Overload: The abundance of fragmented data sources complicates the decision-making process.
These issues can result in delayed responses, increased transmission rates, and greater societal and economic disruption.

Our Solution
Our simulation tool addresses these challenges by:

Multi-Agent Modeling: Simulating individual behaviors and interactions to capture the nuanced spread of diseases.
Policy Impact Analysis: Allowing users to model and compare the effects of various intervention strategies, such as lockdowns, vaccination campaigns, and travel restrictions.
Real-Time Insights: Providing immediate feedback on potential outcomes, helping to adjust policies proactively.
User-Friendly Interface: Designed for policymakers without requiring technical expertise in modeling or epidemiology.

In a world where epidemics can rapidly transcend borders, the ability to make swift, informed policy decisions is crucial. We present a multi-agent epidemic simulation tool to navigate the complexities of epidemic management effectively.

Tech Titens

Unleash the potential of Streamlit for rapid deployment of data applications.

streamlit

CrewAI enhances team collaboration and productivity using AI. It streamlines workflows, automates tasks, and provides real-time insights, making it ideal for organizations of all sizes.

CrewAI

Composio is a versatile platform that enhances AI agents with 100+ tools for tasks like GitHub management, API integration, and automation. It supports major AI frameworks and offers managed authorization and extensibility.

Composio

Multi-Agent Epidemic Simulation Tool

Aquinas revolutionizes social media engagement by leveraging the power of AutoGen, a sophisticated multi-agent AI framework. Our tool continuously monitors Twitter for brand-relevant mentions and hashtags, employing a team of specialized AI agents to analyze tweet content, context, and sentiment. The system then generates witty, on-brand responses that resonate with the audience.

What sets Aquinas apart is its human-in-the-loop approach. While AI does the heavy lifting of tweet analysis and response generation, human operators retain control over the final output. This ensures that all replies align with brand voice and strategy, combining the efficiency of AI with the nuance of human judgment.

Our sleek, user-friendly dashboard provides real-time analytics, allowing social media managers to track engagement metrics, visualize trends, and adjust keywords on the fly. The intuitive interface presents AI-generated responses for quick approval or modification, streamlining the workflow and significantly reducing response times.

Aquinas not only enhances customer interaction but also provides valuable insights into audience sentiment and trending topics. By fostering more personalized and timely interactions, it helps brands build stronger relationships with their followers, ultimately driving engagement and loyalty.

Aquinas is an innovative social media engagement tool that uses AutoGen's multi-agent AI system to analyze tweets, generate witty responses, and enhance brand communication with a human-in-the-loop approval process.

Zarathustra

Redis is an open-source, in-memory data store that provides access to mutable data structures via a set of commands. It offers high performance and scalability, making it a popular choice for use in web applications and other use cases that require fast data access. Redis supports various advanced features such as persistence options, replication, clustering, and pub/sub messaging.

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