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langchain-dependencies

Identify and lock compatible LangChain dependencies across Python and TypeScript ecosystems.

1|Updated Aug 23, 2025
Search Tags:#typescript#versioning#python#dependencies#langchain#framework#environment
One-click install
npx skills add https://github.com/laceto/financialtools --skill langchain-dependencies-laceto
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langchain-dependencies
Source: https://github.com/laceto/financialtools/tree/main/.claude/skills/langchain-dependencies
Command: npx skills add https://github.com/laceto/financialtools --skill langchain-dependencies-laceto

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The LangChain dependency guide helps you select and pin compatible versions across Python and TypeScript projects, preventing upgrades from breaking your stack by clarifying core packages, orchestration choices, and provider integrations.

Core Features & Use Cases

  • Environment requirements and minimum versions for Python and TypeScript ecosystems.
  • Framework Choice guidance between LangGraph and Deep Agents, including recommended accompanying packages.
  • Versioning policy and upgrade strategy for LangChain, LangGraph, and community packages.
  • Environment variables guidance (e.g., LANGSMITH_API_KEY) and common pitfalls during setup.

Quick Start

Install the LangChain core, orchestration package, and a provider package suitable for your project.

Frequently Asked Questions about langchain-dependencies

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

FAQPage Schema
How do I configure compatible LangChain dependencies across Python and TypeScript?▼

You can configure compatible LangChain dependencies by identifying and locking in matching versions for core packages, orchestration layers, and provider integrations. This strategy prevents upgrades from breaking your stack across Python and TypeScript environments.

What's the best way to choose between LangGraph and Deep Agents for my project?▼

Choosing between LangGraph and Deep Agents requires evaluating your orchestration needs alongside recommended accompanying packages. This framework choice dictates your core package versions and environment setup for LangChain workflows.

Why does my LangChain upgrade break my existing Python or TypeScript environment?▼

LangChain upgrades break environments when core packages, orchestration layers, and provider integrations have conflicting versions. Applying a strict versioning policy and upgrade strategy ensures dependencies remain compatible during installation.

Do I need specific environment variables for LangChain setup?▼

You need specific environment variables like LANGSMITH_API_KEY for LangChain setup. Configuring these correctly avoids common pitfalls during package installation and workflow execution across Python and TypeScript projects.

How do I lock LangChain community package versions to avoid conflicts?▼

To lock LangChain community package versions, apply a consistent versioning policy across core, orchestration, and provider packages. This prevents unexpected conflicts and ensures your environment remains stable during upgrades.

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