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Alex1980Alex
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langchain-tutorials

Build, test, and compare RAG and SQL agents with LangChain tutorials.

1|Updated Sep 20, 2025
Search Tags:#langchain#langgraph#tutorial#semantic-search#rag-agent#sql-agent
One-click install
npx skills add https://github.com/Alex1980Alex/1C-Enterprise_Framework --skill langchain-tutorials
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langchain-tutorials
Source: https://github.com/Alex1980Alex/1C-Enterprise_Framework/tree/main/.claude/skills/langchain-tutorials
Command: npx skills add https://github.com/Alex1980Alex/1C-Enterprise_Framework --skill langchain-tutorials

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

LangChain/LangGraph tutorials provide practical, hands-on patterns to build and evaluate RAG agents, SQL agents, and semantic search pipelines, enabling faster experimentation without starting from scratch.

Core Features & Use Cases

  • RAG Agent tutorials: instruct how to configure an agent with retrieval over document corpora and improved queries.
  • SQL Agent tutorials: demonstrate building agents that interact safely with databases, including schema discovery and query execution.
  • Semantic Search & Multi-Agent tutorials: show end-to-end workflows from ingestion to retrieval-to-answer, including multi-agent coordination.

Quick Start

Experiment with the included tutorials by running the example scripts to observe agent behavior.

Frequently Asked Questions about langchain-tutorials

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

FAQPage Schema
How do I build a RAG agent with LangChain for document retrieval?▼

To build a RAG agent with LangChain, configure an agent with retrieval over document corpora to improve queries. These tutorials provide practical patterns and hands-on examples to set up retrieval-augmented generation workflows without starting from scratch.

What's the best way to create a SQL agent using LangGraph?▼

Creating a SQL agent with LangGraph involves building agents that interact safely with databases, including schema discovery and query execution. The tutorials demonstrate practical patterns for safely connecting agents to your database and executing queries.

Do I need a specific LLM provider to run LangGraph multi-agent examples?▼

Yes, running LangGraph multi-agent examples requires Python, LangChain/LangGraph libraries, and access to a compatible LLM provider. You need these dependencies configured in your environment to execute the included sample scripts and observe agent behavior.

How does semantic search workflow integration work in LangChain?▼

Semantic search workflows in LangChain operate end-to-end from data ingestion to retrieval-to-answer. The tutorials show how to implement complete pipelines, including multi-agent coordination across semantic search and voice-enabled scenarios.

Can I use these LangChain tutorials for multi-agent coordination systems?▼

Yes, these LangChain tutorials cover multi-agent coordination across RAG, SQL, and voice-enabled scenarios. They provide hands-on examples and practical patterns to build, test, and compare multi-agent systems within the LangGraph framework.

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