Langchain agent example github. Learn to use LangChain, RAG, and FAISS for code Q&A.

Langchain agent example github. Contribute to openai/openai-cookbook development by creating an account on GitHub. Purpose and Scope The Agent Inbox LangGraph Example showcases a bare A collection of generative UI agents written with LangGraph. Azure OpenAI GPT-4 for intelligent language understanding and generation of SQL queries in PostgreSQL. For detailed information about the system design, see System Architecture. The agent can assist users with finding their account information, completing a loan application, or answering natural language questions while also citing sources for the provided answers. Azure Database for PostgreSQL for data storage and querying. Welcome to "Awesome LagnChain Agents" repository! This repository is dedicated to showcasing the most amazing, innovative, and intriguing LangChain Agents from all over the world. This repository contains sample code to demonstrate how to create a ReAct agent using Langchain. Contribute to langchain-ai/langgraph development by creating an account on GitHub. An examples code to make langchain agents without openai API key (Google Gemini), Completely free unlimited and open source, run it yourself on website. The application showcases a shipping company LangChain and LangGraph SQL agents example. Check out some other full examples of apps that utilize LangChain + Streamlit: Auto-graph - Build knowledge graphs from user-input text (Source code) Web Explorer - Retrieve and summarize insights from the web (Source code) LangChain Teacher - Learn LangChain from an LLM tutor (Source code) Text Splitter Playground - Play with various types of text splitting for RAG (Source code) Tweet Jun 17, 2025 · LangChain supports the creation of agents, or systems that use LLMs as reasoning engines to determine which actions to take and the inputs necessary to perform the action. A production-grade architecture for building an autonomous AI agent that analyzes GitHub repos. Build resilient language agents as graphs. The project provides detailed instructions for setting up the environment and loading travel data, aiming to empower developers to integrate similar agents into their This repository contains examples of using LangChain, a framework for building applications with large language models (LLMs), to create various types of agents. These agents leverage the power of LLMs to perform tasks such as music recommendations, financial data retrieval, and mathematical reasoning. It also includes a simple web interface for interacting with the agent. My goal is to support the LangChain community by giving these fantastic . It's designed to be simple yet informative, guiding you through the essentials of integrating custom tools with Langchain. These evaluators expect you to format your agent's trajectory as a list of OpenAI format dicts or as a list of LangChain BaseMessage classes, and handle message formatting under the hood. Unlimited Open-source Gemini Agents With Langchain - GitHub - ZeroXClem/Gemini-agent-example: Unlimited Open-source Gemini Agents With Langchain This repository demonstrates how to build a multi-agent AI system using: LangChain for natural language to SQL translation. Examples and guides for using the OpenAI API. May 2, 2023 · LangChain is a framework for developing applications powered by language models. May 16, 2025 · Overview Relevant source files This document provides an introduction to the Agent Inbox LangGraph Example, a minimal implementation that demonstrates how to build agent systems with human-in-the-loop capabilities using LangGraph and Agent Inbox. Why do LLMs need to use Tools? Using one of langchain's pre-built agents involves three variables: defining the tools or the toolkit defining the llm defining the agent type This is all really easy to do in langchain, as we will see in the following example. js - langchain-ai/langgraphjs-gen-ui-examples Agent trajectory match evaluators are used to judge the trajectory of an agent's execution either against an expected trajectory or using an LLM. Their framework enables you to build layered LLM-powered applications that are context-aware and able to interact dynamically with their environment as agents, leading to simplified code for you and a more dynamic user experience for your customers. AutoGen for coordinating AI agents in collaborative workflows. Contribute to johnsnowdies/langchain-sql-agent-example development by creating an account on GitHub. (Update when i a The repository contains a bare minimum code example to get started with the Agent Inbox with LangGraph. Currently the OpenAI stack includes a simple conversational Langchain agent running on AWS Lambda and using DynamoDB for memory that can be customized with tools and prompts. This sample solution creates a generative AI financial services agent powered by Amazon Bedrock. The AWS Bedrock stack includes a conversational chain Aug 30, 2023 · Explores the implementation of a LangChain Agent using Azure Cosmos DB for MongoDB vCore to handle traveler inquiries and bookings. Curated list of agents built on LangChain. Ready to support ollama. Learn to use LangChain, RAG, and FAISS for code Q&A. htlxuzp kewrw ouegkx pxkjx aexghz xyb nitabka kzpnpbm etq wgii

26th Apr 2024