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Regression testing for AI agents. Snapshot behavior, diff tool calls, catch regressions in CI. Works with LangGraph, CrewAI, OpenAI, Anthropic.

A toolkit for developing AI agents, including agent-debugger: Terminal debugger for LangGraph & LangChain agents. Debug LLM agents with state inspection, tool calls, semantic breakpoints, and Python program stepping in one Textual UI.

Practical step-by-step LangChain guides

Flakestorm — Automated Robustness Testing for AI Agents. Stop guessing if your agent really works. FlakeStorm generates adversarial mutations and exposes failures your manual tests and evals miss.

Explores the implementation of a LangChain Agent using Azure Cosmos DB for MongoDB vCore to handle traveler inquiries and bookings. The project provides detailed instructions for setting up the environment and loading travel data, aiming to empower developers to integrate similar agents into their solutions.

A production-ready, scalable multi-agent system built with LangGraph Platform, featuring specialized agents, multi-provider LLM support, and complete LangGraph Studio compatibility.

It automatically describes images in PDF files and generates questions from these descriptions. With its advanced RAG structure, it directs these questions directly to PDF text content, providing comprehensive information extraction and analysis.

The personal assistance chatbot integrates appointment creation, Google Calendar event scheduling with Google Meet, and email notifications using the Langchain and Zapier NLA integration.

Hybrid Knowledge Agentic RAG System

Example application for constructing and running an LLM-based LangChain SQL Agent based on GPT-4o mini that can dynamically query a database and invoke multiple visualization tools

Use a RAG Langchain agent that connects to your supermarket's inventory database and get information about product stocks and locations.

LangForge is a comprehensive documentation platform for LangChain and its ecosystem, providing detailed guides, API references, and interactive examples for building with large language models (LLMs).

A Multi-modal chatbot with LangChain, that supports RAG, Paperswithcode, and Image generation using Dall-E-3

This repository hosts a Jupyter notebook that demonstrates the seamless integration of the Bard API with the LangChain library. By leveraging the capabilities of both platforms, we've crafted a custom Language Learning Model (LLM) that allows users to harness the power of Bard within the LangChain ecosystem.

FastAPI application with streaming Langchain agents and Tavily search tool

A repository for final project of NLP Bootcamp at Indonesia AI

Generative AI demos, an example of a langchain based application that implements Retrieval-Augmented-Generation for an enhanced generation. It uses OpenAI model and OpenAI function tool agent. Able to run Ollama Mistral local LLM too.

CodeNova an Ultimate Gen AI project with multiple features that helps developers to get their job ready and also ensure their to help in production level

Welcome to our new Custom WebSearch Agent, now as an easy-to-use Streamlit app! No more sifting through loads of generic results. With this app, you get a search experience that's all about you. It's like having your own personal search assistant right at your fingertips.

This project focuses on developing a real-time, intelligent healthcare assistant powered by Agentic RAG (Retrieval-Augmented Generation) and the LangChain framework. Designed to provide multimodal support—text, image, and document-based inputs—it aims to assist medical personnel and individuals in remote areas.

LLMOps: A production-ready platform for building, deploying, and managing customizable multi-agent AI chatbots. The system leverages modern LLMs, agent frameworks, and search tools to provide interactive, context-aware conversations.

LanchainLLM

All my AI Agent projects in one place. Smart, interactive, and tool-powered! 🚀

FullStack LangChain application using SpringBoot, LangChain4J and React - integrate with internal data and api and upload internal documents for RAG

The Text-to-SQL Agent is designed to to interact with databases using simple, conversational language, eliminating the need for manual query writing.

A trading assistant agent. Powered by Langchain 🦜.

This project focuses on building a system of autonomous agents powered by Large Language Models (LLMs) and LangChain. Each agent is designed to complete specific tasks using various tools, and the agents are decoupled from each other. The architecture follows an event-driven design.

Use a Langchain GPT-agent to search the web with Tavily and answer the prompt including the target-URL.

This project leverages the power of OpenAI's Language Model Agents to create an intelligent SQL query assistant.