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Langchain Dependencies

Official
langchain-ai·vlatest·ai-ml·MIT

Manages and resolves complex Python package dependencies required for LangChain projects, ensuring smooth operation.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add langchain-ai/langchain-skills --skill langchain-dependencies -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

langchain-ai

Matched to the vendor's own GitHub organisation.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned langchain-ai/langchain-skills at 16a992f09a.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
16a992f09a
Manifest
config/skills/langchain-dependencies/SKILL.md
Scanned
1 file, 404 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The langchain-dependencies skill provides the foundational libraries required to build and run LangChain applications, enabling seamless integration of LLMs with external tools. It ensures that all necessary Python packages for chaining prompts, managing memory, and interacting with various data sources are correctly installed and configured.

When to use it

  • Initializing a new LangChain project from scratch to ensure all core components are present.
  • Resolving missing package errors when deploying an agent to a cloud environment or container.
  • Upgrading the stack to access the latest features for model integration or vector store support.
  • Standardizing dependencies across multiple development environments to prevent "it works on my machine" issues.

Key capabilities

  • Installs core LangChain libraries including langchain-core, langchain-community, and langchain-experimental.
  • Configures required external integrations for popular LLM providers, vector databases, and retrieval tools.
  • Manages version compatibility between LangChain and its underlying dependencies like Pydantic or SQLAlchemy.

Example prompts

  • "Install the latest stable version of langchain-core and all community integrations."
  • "Set up a fresh Python environment with langchain-experimental for advanced agent features."
  • "Verify that all necessary dependencies for connecting to Pinecone are installed correctly."

Tips & gotchas

Ensure your Python environment has pip or poetry configured before running installation commands, as this skill relies on package managers. Be mindful of memory usage during installation, as installing the full suite of community integrations can require significant disk space and time.