Deep Research Agent with OpenAI Agents SDK and Firecrawl
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.
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...
A privacy-focused legal analysis team powered by local Ollama models, Agno, and Qdrant vector search to analyze contracts and legal documents offline.
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.
A conversational RAG application that connects to any GitHub repository, allowing developers to query codebases, pull requests, and commit logs with conversational AI.
A Retrieval-Augmented Generation assistant that links to your Gmail inbox to answer natural language queries, summarize threads, and surface priority emails.
A document question-answering tool powered by local or cloud LLMs with RAG to extract answers, summarize sections, and query uploaded PDF files.
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.
An offline document search application that combines keyword retrieval with local dense embeddings and open-source models using RAGLite and Streamlit.
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 high-precision document question-answering system combining BM25 keyword matching with vector embeddings and Claude 3.5 Sonnet via RAGLite.
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.
A document querying service built with Claude 3.5 Sonnet, Ragie.ai, and Streamlit that provides fast and accurate retrieval-augmented responses over ingested URLs.
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...
Pocket Flow: 100-line LLM framework. Let Agents build Agents!.
The agent engineering platform.
100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source.
Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More.
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs.
Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.
📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程.
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience.
The Memory Layer for AI Agents - Drop-in memory infrastructure for AI agents and apps. Context that persists. Built for production.
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
An open-source reference implementation of Flowise for AI and LLM workflows.
LlamaIndex is the document processing platform for AI.
NVIDIA AI Blueprint for video search and summarization (VSS) is a GPU-accelerated reference architecture for building video analytics agents with real-time verified alerts, visual Q&A, and automated reporting.
Resource, examples & tutorials for multimodal AI, RAG and agents using vector search and LLMs.
280+ free n8n automation templates — ready-to-use workflows for Gmail, Telegram, Slack, Discord, WhatsApp, Google Drive, Notion, OpenAI, and more. AI agents, RAG chatbots, email automation, social media, DevOps, and document processing. The largest open-source n8n template collection.
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search.
📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG.
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud.
Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
A lightweight, lightning-fast, in-process vector database.
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows.
[MLsys2026 Best Paper]: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.
An open-source reference implementation of Langgraph for AI and LLM workflows.
35 production-grade agentic AI architectures (Reflexion, LATS, GraphRAG, MemGPT, Voyager, BrowserAgent, ...) — a Python library and runnable textbook with multi-provider LLM support and a 17-task benchmark leaderboard.
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
Evidence-backed use cases, patterns, prompts, and starter code for TypeSafe Jev — a System One model for fast, typed, confidence-aware decisions in software.
A collection of scientific methods, processes, algorithms, and systems to build stories & models.
An AI-powered custom node for ComfyUI designed to enhance workflow automation and provide intelligent assistance.
Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills.
A no-code RAG server that keeps answers in sync with your documents. Works with 8 vector databases. Built on Pathway.