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langchain-dependencies

Manage dependency versions and package selection for LangChain, LangGraph, and LangSmith projects.

2|Updated Apr 3, 2026
Search Tags:#typescript#versioning#python#dependencies#langchain#langgraph
One-click install
npx skills add https://github.com/jxtngx/dgx-lab --skill langchain-dependencies-jxtngx
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langchain-dependencies
Source: https://github.com/jxtngx/dgx-lab/tree/main/.cursor/skills/langchain-dependencies
Command: npx skills add https://github.com/jxtngx/dgx-lab --skill langchain-dependencies-jxtngx

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill resolves the complexity of managing the fragmented LangChain ecosystem, preventing version conflicts and ensuring your project uses the correct, stable package combinations.

Core Features & Use Cases

  • Dependency Validation: Provides clear guidance on minimum versions for LangChain, LangGraph, and LangSmith to ensure compatibility.
  • Framework Selection: Helps you choose between LangGraph and Deep Agents based on your specific orchestration needs.
  • Best Practices: Offers a structured approach to pinning packages, avoiding deprecated community imports, and maintaining LTS releases.

Quick Start

Ask the skill to provide the minimal dependency configuration for a new LangGraph project using Python.

Frequently Asked Questions about langchain-dependencies

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

FAQPage Schema
How do I manage LangChain versions and dependencies to prevent package conflicts?▼

To manage LangChain versions and dependencies effectively, use a structured approach to pin packages and maintain LTS releases. This prevents version conflicts and ensures your project uses correct, stable package combinations across the ecosystem.

What is the minimal dependency configuration needed for a new LangGraph project?▼

The minimal dependency configuration for a new LangGraph project requires specific minimum versions for LangChain, LangGraph, and LangSmith packages. This baseline setup ensures ecosystem compatibility and prevents integration issues.

Do I need LangGraph or Deep Agents for my specific orchestration needs?▼

Choosing between LangGraph and Deep Agents depends on your specific orchestration requirements. LangGraph handles complex stateful workflows, while Deep Agents suit different orchestration patterns within the LangChain ecosystem.

Why does my LangChain project break when I update Python or TypeScript packages?▼

LangChain projects break during updates due to peer dependency mismatches and deprecated community imports. Applying canonical import paths and validating minimum version requirements stabilizes the ecosystem integration.

Can I use deprecated community imports with the latest LangChain LTS releases?▼

Deprecated community imports are not supported with current LangChain LTS releases. To ensure long-term stability, you must use canonical import paths and adhere to peer dependency management best practices.

What's the best way to select compatible packages across the LangChain, LangGraph, and LangSmith ecosystem?▼

The best way to select compatible packages is applying dependency validation across the LangChain, LangGraph, and LangSmith ecosystem. This provides clear guidance on minimum versions to ensure full compatibility.

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