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langchain-dependencies

Plan and lock LangChain-related dependencies for Python and TypeScript projects.

Updated May 25, 2026
Search Tags:#versioning#dependencies#langchain#environment#langgraph#langsmith#deepagents
One-click install
npx skills add https://github.com/lguibr/fh --skill langchain-dependencies-lguibr
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langchain-dependencies
Source: https://github.com/lguibr/fh/tree/main/.agents/skills/langchain-dependencies
Command: npx skills add https://github.com/lguibr/fh --skill langchain-dependencies-lguibr

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps engineers plan, validate, and enforce correct dependencies for LangChain-based projects across Python and TypeScript, ensuring compatibility between core packages (langchain, langchain-core, langsmith) and orchestration layers (LangGraph or Deep Agents) while guiding upgrades and tooling choices.

Core Features & Use Cases

  • Dependency planning: identify required packages and minimum versions for LangChain, LangGraph, LangSmith, and Deep Agents.
  • Environment guidance: specify Python and Node runtime requirements and align with long-term support releases to minimize upgrade risk.
  • Versioning strategy: provide pinned ranges for community tooling and best practices for cross-language projects.
  • Use Case: when starting a new LangChain project, generate a complete bill of materials for Python and TypeScript stacks.

Quick Start

Determine your project stack (Python or TypeScript) and outline the baseline dependencies and environment requirements to initialize your setup.

Frequently Asked Questions about langchain-dependencies

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

FAQPage Schema
How do I plan dependencies for a new LangChain project?▼

To plan dependencies for a new LangChain project, identify required packages and minimum versions for LangChain, LangGraph, LangSmith, and Deep Agents. This generates a complete bill of materials covering version pinning and environment requirements.

What are the minimum version requirements for LangChain and LangGraph?▼

Minimum version requirements for LangChain and LangGraph ensure compatibility between core packages and orchestration layers. Specifying pinned ranges for these dependencies prevents conflicts and aligns with long-term support releases.

Can I use LangSmith and Deep Agents with a TypeScript stack?▼

Yes, LangSmith and Deep Agents work with TypeScript stacks alongside Python. Dependency planning covers both environments, ensuring correct package versions and Node runtime requirements are defined for cross-language projects.

What is the best way to pin LangChain community tooling versions?▼

The best way to pin LangChain community tooling versions is to specify pinned ranges in your project setup. This minimizes upgrade risk by aligning with long-term support releases and documenting best practices for versioning.

Why does my LangChain environment break after upgrading core packages?▼

LangChain environments break after upgrading core packages due to compatibility issues between langchain-core and orchestration layers like LangGraph. Enforcing correct dependency versions and pinned ranges validates compatibility and prevents these conflicts.

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