EDA Autogen App is an interactive Streamlit tool that performs automatic Exploratory Data Analysis (EDA) using multi-agent AI and LLMs. Users can upload CSV datasets and watch agents collaboratively generate code, execute analyses, visualize data, and provide actionable insights—all in real time. Supports local (Ollama) and cloud (OpenAI, Gemini)
AutoGen travel planner will utilize multiple AI agents, each with a specific role, to collaboratively create a comprehensive travel itinerary.
a template for multi-agent collaboration using chainlit, llamaindex, autogen
A hands-on AutoGen Frameworks suite featuring practical notebooks and agent projects: explore single/multi-agent chat, async workflows, human-in-the-loop, data analysis (Analyzer GPT), DSA solving, travel planning, and advanced agent orchestration all in one place.
This project is a chatbot implementation using Microsoft's AutoGen framework and Azure OpenAI services. The chatbot is designed to handle various tasks, including retrieving product information, policy details, claim details, and more.
DSA Solving Multi Agent System using Microsoft Autogen Framework
Reanalyze Risk Tolerance Using AI Agentic Workflow: This project leverages AI agents and advanced language models to reevaluate user risk tolerance based on financial data and demographic information extracted from JSON files. Utilizing Microsoft Autogen and Llama3.1 8b from Groq API.
ArxivAgent is a multi-agent system powered by GPT-4o and AutoGen that automates ArXiv paper search and summarization into literature review format using intelligent agent collaboration.
Multi-Agent AI that cracks DSA problems, explains the logic, and runs the code for you.
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