Retrieval Augmented Generation architectures, hybrid vector-BM25 search, reranking, and contextual retrieval.
A powerful research assistant that leverages OpenAI's Agents SDK and Firecrawl's deep research capabilities to perform comprehensive web research on any topic and any question.
A Streamlit application that provides comprehensive design analysis using a team of specialized AI agents powered by Google's Gemini model. This application leverages multiple specialized AI agents to provide comprehensive analysis of...
This Streamlit application leverages multiple AI agents to create comprehensive meeting preparation materials. It uses OpenAI's GPT-4, Anthropic's Claude, and the Serper API for web searches to generate context analysis, industry...
Third-party tools allow you to integrate existing tool ecosystems from frameworks like LangChain, CrewAI, and others. This dramatically expands your agent's capabilities by leveraging battle-tested tools from the broader AI community.
This Streamlit app enables you to engage in interactive conversations with arXiv, a vast repository of scholarly articles, using GPT-4o. With this RAG application, you can easily access and explore the wealth of knowledge contained...
Streamlit app that allows you to chat with a Substack newsletter using OpenAI's API and the Embedchain library. This app leverages GPT-4 to provide accurate answers to questions based on the content of the specified Substack newsletter.
LLM app with RAG to chat with YouTube Videos with OpenAI's gpt-4o, mem0/embedchain as memory and the youtube-transcript-api. The app uses Retrieval Augmented Generation (RAG) to provide accurate answers to questions based on the content...
This Streamlit application implements a fully local ChatGPT-like experience using Llama 3.1, featuring personalized memory storage for each user. All components, including the language model, embeddings, and vector store, run locally...
An agentic RAG application built with the Agno framework, featuring GPT-5 and LanceDB for efficient knowledge retrieval and question answering.
A RAG Agentic system built with the new Gemini 2.0 Flash Thinking model and gemini-exp-1206, Qdrant for vector storage, and Agno (phidata prev) for agent orchestration. This application features intelligent query rewriting, document...
AI Blog Search is an Agentic RAG application designed to enhance information retrieval from AI-related blog posts. This system leverages LangChain, LangGraph, and Google's Gemini model to fetch, process, and analyze blog content,...
This Streamlit application implements an Autonomous Retrieval-Augmented Generation (RAG) system using OpenAI's GPT-4o model and PgVector database. It allows users to upload PDF documents, add them to a knowledge base, and query the AI...
A Streamlit app that integrates Contextual AI's managed RAG platform. Create a datastore, ingest documents, spin up an agent, and chat grounded on your data.
A sophisticated Retrieval-Augmented Generation (RAG) system that implements a corrective multi-stage workflow using LangGraph. This system combines document retrieval, relevance grading, query transformation, and web search to provide...
A powerful reasoning agent that combines local Deepseek models with RAG capabilities. Built using Deepseek (via Ollama), Snowflake for embeddings, Qdrant for vector storage, and Agno for agent orchestration, this application offers both...
A Streamlit application demonstrating how Knowledge Graph-based Retrieval-Augmented Generation (RAG) provides multi-hop reasoning with fully verifiable source attribution.
A powerful document Q&A application that leverages Hybrid Search (RAG) and local LLMs for comprehensive answers. Built with RAGLite for robust document processing and retrieval, and Streamlit for an intuitive chat interface, this system...
An open-source agentic RAG system for mathematical problem solving and symbolic reasoning using LLMs and calculation tools.
This is a multimodal RAG app built with Gemini Embedding 2 and Google ADK. Add text, URLs, PDFs, images, audio, or video; ask a question; and get a grounded answer with clear citations.
PharmaQuery is an advanced Pharmaceutical Insight Retrieval System designed to help users gain meaningful insights from research papers and documents in the pharmaceutical domain.
This RAG Application demonstrates how to build a powerful Retrieval-Augmented Generation (RAG) system using locally running Qwen 3 and Gemma 3 models via Ollama. It combines document processing, vector search, and web search...
A RAG Agentic system built with Cohere's new model Command-r7b-12-2024, Qdrant for vector storage, Langchain for RAG and LangGraph for orchestration. This application allows users to upload documents, ask questions about them, and get...
A Streamlit application that demonstrates an advanced implementation of RAG Agent with intelligent query routing. The system combines multiple specialized databases with smart fallback mechanisms to ensure reliable and accurate...
A powerful document Q&A application that leverages Hybrid Search (RAG) and Claude's advanced language capabilities to provide comprehensive answers. Built with RAGLite for robust document processing and retrieval, and Streamlit for an...
A small, framework-agnostic RAG failure diagnostics clinic. You paste a real bug description from your LLM + RAG pipeline.
This Streamlit app answers questions from uploaded PDFs or a documentation URL. Every response is a validated Answer object with exact source quotes, chunk IDs.
A powerful visual Retrieval-Augmented Generation (RAG) system that utilizes Cohere's modern Embed-4 model for multimodal embedding and Google's efficient Gemini 2.5 Flash model for answering questions about images and PDF pages.
This Streamlit app demonstrates an agentic Retrieval-Augmented Generation (RAG) Agent using Google's EmbeddingGemma for embeddings and Llama 3.2 as the language model, all running locally via Ollama.
Streamlit app that allows you to chat with any webpage using local Llama-3.1 and Retrieval Augmented Generation (RAG). This app runs entirely on your computer, making it 100% free and without the need for an internet connection.
This application implements a Retrieval-Augmented Generation (RAG) system using Llama 3.2 via Ollama, with Qdrant as the vector database. Built with Agno v2.0.
4. Run the Streamlit app streamlit run ragapp.py.
A Streamlit application that helps users estimate the amount of term life insurance they may need and surfaces currently available policy options. The app is powered by the Agno agent framework, uses OpenAI GPT-5 as the LLM, the E2B...
A multi-agent research application built with OpenAI's Agents SDK and Streamlit. This application enables users to conduct comprehensive research on any topic by leveraging multiple specialized AI agents.
The AI Reasoning Agent leverages advanced AI models to provide insightful reasoning and decision-making capabilities. This agent is designed to assist users in various analytical tasks by processing information and generating structured...
