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langchain-dependencies

Guide dependency setup for LangChain, LangGraph, LangSmith, and Deep Agents across Python and TypeScript.

2|Updated Mar 7, 2026
Search Tags:#typescript#package management#python#dependencies#langchain#langgraph#langsmith
One-click install
npx skills add https://github.com/Lincyaw/AgentM --skill langchain-dependencies-lincyaw
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langchain-dependencies
Source: https://github.com/Lincyaw/AgentM/tree/main/.claude/skills/langchain-dependencies
Command: npx skills add https://github.com/Lincyaw/AgentM --skill langchain-dependencies-lincyaw

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you navigate the complexities of setting up and managing dependencies for the LangChain ecosystem, ensuring compatibility and efficient project setup.

Core Features & Use Cases

  • Dependency Management: Provides guidance on required packages, minimum versions, and best practices for LangChain, LangGraph, LangSmith, and Deep Agents.
  • Environment Setup: Details runtime requirements for both Python and TypeScript/Node.js environments.
  • Framework Choice: Clarifies when to use LangGraph versus Deep Agents.
  • Use Case: When starting a new project using LangChain, use this Skill to determine the exact packages and versions needed for your Python environment, including model providers and common tools.

Quick Start

Install the core LangChain Python dependencies for a new project.

Frequently Asked Questions about langchain-dependencies

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

FAQPage Schema
How do I manage dependencies when starting a new LangChain project in Python?▼

To manage LangChain dependencies, install the core package and specify required minimum versions for model providers and common tools. Use minimal project templates to ensure environment compatibility and avoid legacy version conflicts.

What's the difference between using LangGraph and Deep Agents for my application?▼

LangGraph and Deep Agents serve different framework choices within the ecosystem. Guidance clarifies when to use LangGraph versus Deep Agents based on your specific workflow requirements and dependency setup.

Why do my LangChain community package imports fail after updating?▼

Import failures often stem from common mistakes like pinning legacy community package versions or using incorrect import paths. Ensure you follow versioning policies and correct import structures to resolve these setup issues.

What environment variables do I need to configure for LangSmith and LangChain?▼

Configuring environment variables for LangSmith and LangChain requires setting up specific API keys and tracing configurations. Proper environment setup ensures framework integrations function correctly without authentication errors.

Do I need to pin specific versions of LangChain packages to avoid compatibility issues?▼

Yes, pinning specific versions is crucial to avoid compatibility issues. The skill provides versioning policies and highlights common mistakes related to legacy versions and community package pinning for stable project setup.

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