Langchain Playground

About

This project serves as a comprehensive testing ground and demonstration for building applications with large language models. It showcases integrations with core LLM frameworks like LangChain.js and LangGraph for advanced workflow orchestration, enabling multi-step processes. The tool offers both REST API endpoints and a Slack bot interface for interacting with diverse language models and custom workflows, exemplified by a New Relic log analysis system and a Retriever-Augmented Generation (RAG) implementation for querying documents. It also highlights the integration of Model Context Protocol (MCP) tools and support for various LLM providers and services.

Key Features

• Supports multiple LLM providers including OpenAI, Ollama, and Groq
• Features a Retriever-Augmented Generation (RAG) system for document querying
• Implements advanced workflows like New Relic log analysis using LangGraph
• 4 GitHub stars
• Provides both REST API endpoints and Slack bot functionality
• Integrates LangChain.js and LangGraph for LLM application development

Use Cases

• Developing and testing complex LLM-powered workflows with LangGraph
• Building interactive Slack bots capable of advanced conversational AI
• Implementing and experimenting with Retriever-Augmented Generation (RAG) systems