skills.rest
ThiNepo
ThiNepoCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

langchain-fundamentals

Create and manage LangChain agents with tools and middleware.

2|Updated Sep 9, 2024
Search Tags:#middleware#ai development#langchain#llm#agents#tools
One-click install
npx skills add https://github.com/ThiNepo/prompt-caller --skill langchain-fundamentals-thinepo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langchain-fundamentals
Source: https://github.com/ThiNepo/prompt-caller/tree/main/.continue/skills/langchain-fundamentals
Command: npx skills add https://github.com/ThiNepo/prompt-caller --skill langchain-fundamentals-thinepo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides the foundational knowledge and tools to build robust, production-ready agents using LangChain, enabling complex task automation and conversational AI applications.

Core Features & Use Cases

  • Agent Creation: Utilize create_agent() for streamlined agent construction, managing the agent loop, tool execution, and state.
  • Tool Definition: Define custom tools using @tool (Python) or tool() (TypeScript) for agents to interact with external functionalities.
  • Middleware Integration: Implement middleware patterns for advanced control flows, including human-in-the-loop approvals and error handling.
  • Structured Output: Ensure agents return data in a predictable, typed format using response_format or with_structured_output().
  • Use Case: Develop a customer support agent that can search internal knowledge bases, interact with APIs, and provide structured responses, with an option for human review before sending critical information.

Quick Start

Use the langchain-fundamentals skill to create a basic agent that can search the web and respond to user queries.

Frequently Asked Questions about langchain-fundamentals

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

FAQPage Schema
How do I build production LangChain agents using create_agent?▼

Use create_agent() to build production LangChain agents by managing the agent loop, tool execution, and state automatically. It provides streamlined construction for complex task automation and robust conversational AI applications.

What is middleware in LangChain and how does it control agent workflows?▼

Middleware in LangChain implements advanced control flows for agent workflows, enabling custom processes like human-in-the-loop approvals and error handling. It intercepts the agent loop to manage execution and interactions.

How do I define custom tools for LLM agents in Python and TypeScript?▼

Define custom tools for LLM agents using the @tool decorator in Python or the tool() function in TypeScript. This allows agents to interact with external functionalities like APIs and search engines during task execution.

How do I ensure LangChain agents return structured output in a predictable format?▼

Ensure LangChain agents return structured output in a predictable, typed format using response_format or with_structured_output(). This guarantees consistent data schemas for downstream application integration.

Can I implement human-in-the-loop approvals for LangChain tools?▼

Yes, you can implement human-in-the-loop approvals for LangChain tools using middleware integration. This pattern allows human review before agents execute critical actions or send sensitive information.

Related Skills

Explore More Software Engineering Skills→
HemantSudarshanHemantSudarshan

langfuse

Instrument LLM calls for tracing and observability in Python or TypeScript pipelines.

Community
Advanced
Tencent-RTCTencent-RTC
11

ai-custom-service-skill

Build a voice AI customer service agent using TRTC Conversational AI.

Official
Intermediate
vuralserhat86vuralserhat86
43

rag_implementation

Implement RAG systems with vector databases, semantic search, and reranking strategies.

Community
Advanced
EanLeeEanLee

ai-agents-architect

Design autonomous AI agents with tool use, memory, planning, and multi-agent orchestration.

Community
Advanced