Llamaindex agents

LlamaIndex is the leading document agent and OCR platform

Build ChatGPT over your data, all with natural language

The easiest way to use Agentic RAG in any enterprise

Data framework for your LLM applications. Focus on server side solution

Deploy your agentic worfklows to production

This repository provides programs to build Retrieval Augmented Generation (RAG) code for Generative AI with LlamaIndex, Deep Lake, and Pinecone leveraging the power of OpenAI and Hugging Face models for generation and evaluation.

ParseBench - A Document Parsing Benchmark for AI Agents

Run Claude Code/Codex within AgentFS, orchestrated by LlamaIndex Workflows

LLM을 활용한 실전 AI 애플리케이션 개발

⚡Ship RAG Solutions Quickly and effortlessly

Full stack advanced chatbot over LlamaIndex.TS documentation with preview feature using Multi-documents-agents, bootstrapped with create-llama

An agentic AI application that allows you to chat with your papers and gather also information from papers on ArXiv and on PubMed

This project enhances the construction of RAG applications by addressing challenges, improving accessibility, scalability, and managing data and user access. It uses Django, Llamaindex, and Google Drive for effective database management.

Open Source, Self-Hosted, AI Search and LLM.txt for your website

Local llamaindex RAG to assist researchers quickly navigate research papers

XRAG: eXamining the Core - Benchmarking Foundational Component Modules in Advanced Retrieval-Augmented Generation

Using LlamaIndex, Redis, and OpenAI to chat with PDF documents. Supplementary material for blog post on Microsoft Developer Blog

Complete example of how to build an Agentic RAG architecture with Redis, Amazon Bedrock, and LlamaIndex.

Load a PDF file and ask questions via llama_index and GPT

linkedin-jobs-RAG

The library for character-driven AI experiences.

The library for character-driven AI experiences.

OpenAI document chatbot using llama-index, pinecone and chainlit. With incremental features, giving you the tools to go from a basic RAG into an advanced one.

This sample shows how to quickly get started with LlamaIndex.ai on Azure 🚀

Agentic RAG to help you build a startup🚀

This project involves using llamaindex Multi Agents concierge system and Qdrant vector database to customize the RAG application with user preferences over LLMs, Embeddings, Search types, and Reranking Models.

A collection of apps powered by the LlamaIndex LLM framework.

Jupyter notebooks for course Building and Evaluating Advanced RAG Applications, taught by Jerry Liu (Co-founder and CEO of LlamaIndex) and Anupam Datta (Co-founder and chief scientist of TruEra).

An interactive integration of yFiles for HTML with LlamaIndex to visualize the knowledge graph used for query resolution.

AI tour planner agent using LlamaIndex Workflow

A virtual agent for your virtual books📚

ACP wrapper for LlamaIndex Agent Workflows

LLM Chatbot w/ Retrieval Augmented Generation using Llamaindex. It demonstrates how to impl. chunking, indexing, and source citation.

Chat with your PDF files using LlamaIndex, Astra DB (Apache Cassandra), and Gradient's open-source models, including LLama2 and Streamlit, all designed for seamless interaction with PDF files.

Diagnose the performance of your RAG🩺

Tailored cloud solutions based on use case, cost, and preferences using natural language with Agentic AI to research, design, price, diagram, and report an optimized result.

Learn how to talk to Django as any human should -- e.g. Semantic Search and Text-to-SQL.

This is a LlamaIndex project bootstrapped with create-llama to act as a full stack UI to accompany Retrieval-Augmented Generation (RAG) Bootstrap Application.

Match your resume with a job, effortlessly

Simple, High Quality, Open Source RAG solution for chatting with your documents

Multimodal RAG ingests PDFs and generates combined text and image outputs by retrieving and grounding relevant information from the documents.

A RAG system designed to process documents with multimodal content. It can generate factual, context-aware answers to user queries, based on the documents texts, tables, figures, ...

A tool that converts scientific PDFs into plain text for your LLM-related needs, such as building RAGs or agents for academic knowledge. It was developed in collaboration with the LlamaIndex team.

Advanced Coding AI Assistant that uses a Gradio interface to stream coding related responses. ChatRAG supports local and API inference and pulls context from GitHub Repos and local files.

A Web-UI for Llama_index. Allow ChatGPT to access your own database.

Australian Tax Office (ATO) chatbot using LlamaIndex RAG and OpenAI. Features automated documentation processing with ZenML pipelines, Qdrant vector storage, and Streamlit interface. Built for accurate tax information retrieval and natural language query processing.

This playbook teaches you how to compose Tableau's varied product capabilities into applications that thrill customers, coworkers and friends!

Testbed for multimodal retrieval augmented generation techniques with FiftyOne, LlamaIndex, and Milvus

This repository contains code for how to store and query your own data using OpenAI Embeddings and Supabase using JavaScript.

Perform RAG (Retrieval-Augmented Generation) from your PDFs using this Colab notebook! Powered by Llama 2

A RAG implementation on Llama Index using Qdrant vector stores as storage. Take some pdfs, store them in the db, use LLM to inference.

Production-ready Agentic AI ChatBot using Llamaindex and Groq-Llama 3.3

Intuitive RAG system on top of LllamaIndex

A sample app for the Retrieval-Augmented Generation pattern using LlamaIndex.ts, running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences using your own data.

A large model app. Integrating various capabilities. Highly scalable, Highly compatible.

A RAG system is just the beginning of harnessing the power of LLM. The next step is creating an intelligent Agent. In Agentic RAG the Agent makes use of available tools, strategies and LLM to generate response in a specialized way. Unlike a simple RAG, an Agent can dynamically choose between tools, routing strategy, etc.

EduBot is a powerful RAG (Retrieval-Augmented Generation) chatbot that utilizes the latest SOTA models to provide a seamless and interactive learning experience.

LLM Chatbot with Retrieval Augmented Generation using Llamaindex. It works both in online and offline mode.

Taking advantage of LlamaIndex's in-context learning paradigm, LlamaDoc empowers users to input PDF documents and pose any questions related to the content. The tool leverages the LLama Index's reasoning capabilities to provide intelligent responses based on the contextual understanding of the LLM.

🧠 Enterprise AI-Enhanced Development Platform with GraphRAG, LlamaIndex, Multi-Tenant Architecture, and Advanced Security & Compliance. Transform your development workflow with persistent memory, intelligent automation, and 99.9% uptime.

This project has implemented the RAG function on Jetson and supports TXT and PDF document formats. It uses MLC for 4-bit quantization of the Llama2-7b model, utilizes ChromaDB as the vector database, and connects these features with Llama_Index. I hope you like this project.

Chat with Time-Series Data in PostgreSQL using LlamaIndex and Timescale Vector

A simple ReAct agent that has access to LlamaIndex docs and to the internet to provide you with insights on LlamaIndex itself.

Question-Answering App Over Your Own Data with LLamaindex and ElasticSearch !

Automate Your GitHub Flows with MCP!

A production-ready RAG (Retrieval Augmented Generation) system for chatting with your documents

A collection of Python SDKs that enable developers to build and deploy agents to the UiPath Cloud Platform using different agent frameworks

2026 C 题 F 奖得主开发的数学建模/MCM/ICM O 奖论文 RAG 问答引擎：基于 LlamaIndex 章节级检索，支持年份/题号/章节过滤、建模方法/灵敏度分析/写作结构拆解，帮数模备赛快速复盘高分美赛论文

Doppalf is a RAG powered AI chat bot application

The repo provides the code for Qdrant for efficient image indexing and retrieval using models such as ColPali, ColQwen, and VDR-2B-Multi-V1, jina embeddings v4 etc enhancing multimodal search capabilities across various applications.

llama-index-go is a data framework for your LLM applications for Golang

A complete RAG microservice that ingests from multiple sources, stores embeddings in PGVector with hybrid search, and provides both raw chunk retrieval and LLM-powered answer generation. Built with FastAPI, Celery, Redis, and LlamaIndex. Production-ready with rate limiting, health checks, and Docker deployment.

Example of use llama-index in Python desktop application

RAG-API: A production-ready Retrieval Augmented Generation API leveraging LLMs, vector databases, and hybrid search for accurate, context-aware responses with citation support.

Chat with Lex! A RAG app, using HyDE with milvus DB for vector store, VLLM for LLM inference, and FastEmbed for Embeddings!

All-in-one intelligent assistant powered by LlamaIndex — RAG, GraphRAG, NL2SQL, Skills & Memory with multimodal support.

A simple AgenticAI RAG agent showcasing autonomous reasoning and decision-making by integrating thought, logic, and action in real-time tasks.

Streamlined Development with AI An all-in-one platform integrating LLMs for code generation, reviews, documentation, testing, profiling, and security scanning. Features a Streamlit interface with vector-based indexing using Hugging Face and LlamaIndex for efficient, context-aware operations.

Text Classification using LlamaIndex and Gradio

All code to get your own RAG functional

🚀 企业级私有化 RAG 知识库系统 | 💯 纯离线部署、无需联网 | 🔐 支持 LDAP/AD 统一认证与 RBAC 部门级权限隔离 | ⚡️ 基于 LlamaIndex + Ollama + BGE-M3/Rerank | 📝 支持多格式文档解析、上下文对话记忆及精准的 PDF 原文溯源高亮 | 📊 内置数据可视化仪表盘（🚀 Enterprise RAG Knowledge Base. 💯 Fully offline/air-gapped deployment. 🔐 Features LDAP/AD integration, RBAC & Department Isolation. ⚡️ Powered by LlamaIndex, Ollama, and Local R

Deployed RAG platform for document intelligence with hybrid semantic + BM25 retrieval, reranking, citations, and confidence thresholds.

Local RAG legal assistant for private document Q&A, built with React, FastAPI, LlamaIndex, Ollama, Qdrant, Redis/RQ, and Docker Compose.

ResuMate: AI-powered resume screening app using Streamlit, OpenAI, and LlamaIndex. Automate candidate evaluation and boost hiring efficiency.

Gemini Pro LLM and Pinecone Vector Database for fast and performant Retrieval Augmented Generation (RAG) with LlamaIndex

Modular role‑playing chatbot framework built on LlamaIndex & Melobot — supports RAG‑driven role‑play and general QA, with built‑in scheduling (including daily RSS news aggregation) and admin features, offering both OneBot V11 (QQ) and CLI adapters.

Techniques and workflows for building an LLM-powered RAG application using LlamaIndex.

Implementation of "Building Agentic RAG with LlamaIndex" offered by DeepLearning.AI focusing on developing intelligent research agents using the Retrieval-Augmented Generation (RAG) framework.

SAIRA Project, Generative Artificial Intelligence, Fall 2023, Innopolis University

Teaching Tool: Local RAG and LLM Chat over Logseq with LlamaIndex + Ollama + Chroma

FastAPI + Hugging Face Transformers + LlamaIndex

ZeusDB vector database integration for LlamaIndex. Connect LlamaIndex's RAG framework with enterprise-grade vector database capabilities.

React Agentic RAG app using LlamaIndex and OpenAI

RAG with open source LLM mistral loaded through Ollama and built on LlamaIndex and served on Chainlit

Rag Application with Multi-Agent Orchestrator

A friendly bot that summarizes your files and answers your questions - without judging your terrible taste in fonts!

AI Tool RAG System: LlamaIndex-powered discovery engine for AI tools with Telegram bot interface using NeMo Guardrails

A RAG-based conversational AI for knowledge seekers and autodidactic learners.

A simple AgenticAI agent showcasing autonomous reasoning and decision-making by integrating thought, logic, and action in real-time tasks.

This project demonstrates how to build an intelligent customer support agent using LlamaIndex, Groq’s LLaMA 3.3 70B, and HuggingFace Embeddings. The agent can answer questions about orders, return policies, delivery dates, and customer support information by combining function-calling tools and a vector-based RAG setup.