A simple ReAct agent that has access to LlamaIndex docs and to the internet to provide you with insights on LlamaIndex itself.
LLM OSINT is a proof-of-concept method of using LLMs to gather information from the internet and then perform a task with this information.
React AI Agent with Long-Term Memory and Tool calling
The Financial Analysis Crew is a Streamlit app that simplifies financial stock analysis. With the power of LLM-driven agents, users can seamlessly gather and analyze stock market data to generate comprehensive financial insights. Perfect for investors, analysts, and anyone interested in making data-driven financial decisions.
This repository contains a Python application using LangChain to create a multi-agent system for answering queries with Yahoo Finance News and Wikipedia
This project implements a travel chatbot powered by the RAG (Retrieve and Generate) chain, providing real-time information retrieval using various tools and the ability to fetch weather reports.
An AI-powered investment analysis tool 📈 that leverages simple ReAct AI agent flow framework and financial analysis techniques to provide comprehensive portfolio insights. This intelligent agent helps investors make data-driven decisions by offering deep portfolio risk assessment, stock profiling, and personalized recommendations.
Effortlessly create functional documentation with AI and integrate directly with Jira. Generate, refine, and export User Stories to your Jira project in just a few clicks! 🚀
A pure Python implementation of ReAct agent without using any frameworks like LangChain. It follows the standard ReAct loop of Thought, Action, PAUSE, and Observation. The agent utilizes multiple tools, including Calculator, Wikipedia, Web Search, and Weather. A web UI is also provided using Streamlit.
Helping Farmers Around the World. Sandworm restores and preserves agricultural ecosystems with AI.
React&RAG Llama Crew is an AI-powered system using LlamaIndex, RAG, and Hugging Face embeddings for code retrieval, analysis, and generation. A multi-agent crew—Llama3.2, CodeLlama, Ollama, and ReActAgent—handles queries, documentation, and structured code generation. 🚀
A pure Python implementation of ReAct agent without using any frameworks like LangChain. It follows the standard ReAct loop of Thought, Action, PAUSE, and Observation. The agent utilizes multiple tools, including Calculator, Wikipedia, Web Search, and Weather. A web UI is also provided using Streamlit.
Application that generates automatic responses to Amazon Lex messages using generative AI.
Agente Conversacional para Exploração de Vídeos do YouTube: Um assistente conversacional que utiliza transcrições de vídeos do YouTube para responder perguntas, fornecer resumos e destacar momentos importantes com timestamps. Ideal para navegar e compreender conteúdos de vídeos de forma eficiente.
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