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langchain

Build LLM-powered applications with RAG, tool calling, and memory management.

6|3|Updated Jan 29, 2026
Search Tags:#RAG#tool calling#memory management#large language models#LLM applications
One-click install
npx skills add https://github.com/jonnabio/ace-framework --skill langchain-jonnabio
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langchain
Source: https://github.com/jonnabio/ace-framework/tree/main/.ace/packs/ai-research/langchain
Command: npx skills add https://github.com/jonnabio/ace-framework --skill langchain-jonnabio

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires langchain, langchain-core, langchain-openai, langchain-anthropic, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill unit provides a framework for building applications that leverage large language models (LLMs), enabling rapid prototyping and production deployment.

Core Features & Use Cases

  • Multi-provider Support: Integrates with OpenAI, Anthropic, and Google for easy provider switching.
  • RAG Capabilities: Implements Retrieval-Augmented Generation for powerful applications like chatbots and Q&A systems.
  • Tool Calling: Enables calling external tools for enhanced functionality and context management.
  • Memory Management: Offers persistent memory for conversational histories.
  • Use Case: Develop a chatbot that can interact with a user, retrieve information from a knowledge base, and provide context-aware responses.

Quick Start

Install the langchain package and start using it for your application development.

Frequently Asked Questions about langchain

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build LLM applications with retrieval-augmented generation and memory management?▼

The framework supports RAG capabilities for knowledge base retrieval, tool calling for external functions, and persistent memory management for conversational histories.

Can I use this framework to integrate both OpenAI and Anthropic models in my application?▼

Yes, the framework provides multi-provider support for OpenAI and Anthropic, allowing developers to easily switch between LLM providers within their applications.

What is the best way to add tool calling and external context management to large language models?▼

The framework enables tool calling to connect external tools for enhanced functionality and context management, extending LLM capabilities within your application architecture.

Does this LLM framework support developing chatbots that retrieve information from a knowledge base?▼

Yes, the framework implements Retrieval-Augmented Generation (RAG) specifically for building chatbots and Q&A systems that retrieve information from a knowledge base.

What dependencies do I need to install to start building LLM-powered applications?▼

You need to install the langchain package and its core dependencies, including langchain-core, langchain-openai, and langchain-anthropic, to start building LLM-powered applications.

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