langchain

Structured Output Is All You Need!

This template demonstrates how to create a collaborative team of AI agents that work together to process, analyze, and generate insights from documents.

The runtime reliability layer for AI agents.

Natural language querying allows users to interact with databases more intuitively and efficiently. By leveraging the power of LangChain, SQL Agents, and OpenAI’s Large Language Models (LLMs) like GPT, we have created an application that enable users to query databases using NLP

One chat interface across OpenAI, Anthropic and Gemini — with tools, web browsing and shared threads. Built on LangChain.

instinct.cpp provides ready to use alternatives to OpenAI Assistant API and built-in utilities for developing AI Agent applications (RAG, Chatbot, Code interpreter) powered by language models. Call it langchain.cpp if you like.

Opinionated sample on how to build and deploy a RAG application with Amazon Bedrock and OpenSearch

GenAI Experimentation

Multi-Agent Systems with Google's Agent Development Kit + A2A + MCP

Go SDK for interacting with the MCP Toolbox for Databases.

This repository demonstrates the construction of a state-of-the-art multimodal search engine, leveraging Amazon Titan Embeddings, Amazon Bedrock, and LangChain.

Open source authorization engine for AI agents. Confidence-aware gating · Human-in-the-loop review · Policy-as-code · Full audit trail

Build document-native LLM applications

Agentic memory for CTI in Python — STIX knowledge graphs, threat-actor alias resolution, offline-first RAG, MCP server for Claude Code and LangChain agents

Annotation meets Large Language Models (ChatGPT, GPT-3 and alike).

This project is a comprehensive recruitment and interview assistance system developed based on large models and agents, leveraging the langgraph and llamaindex agent frameworks. It aims to enhance job search efficiency and interview performance by automating and intelligentizing the entire interview process. it is China Software Cup A3 competition

GPTStonks is a financial chatbot powered by LLMs and enhanced with data frameworks. It provides natural language conversation capabilities for financial topics, making it an ideal choice for a wide range of financial applications.

The LangChain wrapper of Milvus vector database for efficient vector search, full-text search, hybrid retrieval and RAG.

Running llama3 using Ollama-Python, Curl, LangChain, Chroma, and User interface.

This library exposes PAPA, your Personal Assistant powered by Private AI, which can be used in any browser environment and completely offline