name: langchain-dependencies description: "INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both Python and TypeScript."

Key principles:

• LangChain 1.0 is the current LTS release. Always start new projects on 1.0+. LangChain 0.3 is legacy maintenance-only — do not use it for new work.
• langchain-core is the shared foundation: always install it explicitly alongside any other package.
• langchain-community (Python only) does NOT follow semantic versioning; pin it conservatively.
• LangGraph vs Deep Agents: choose one orchestration approach based on your use case — they are alternatives, not a required stack (see Framework Choice below).
• Provider integrations (model, vector store, tools) are installed separately so you only pull in what you use. </overview>

Framework Choice

Both sit on top of langchain + langchain-core + langsmith. </framework-choice>

Core Packages

Python — always required

Python — orchestration (pick one)

Python — model providers (pick the one(s) you use)

Python — common tool & retrieval packages

These packages have tighter compatibility requirements — use the latest available version unless you have a specific reason not to.

langchain-community stability note: This package is NOT on semantic versioning. Minor releases can contain breaking changes. Prefer dedicated integration packages (e.g. langchain-chroma, langchain-tavily) when they exist — they are independently versioned and more stable.

TypeScript — always required

TypeScript — orchestration (pick one)

TypeScript — model providers (pick the one(s) you use)

TypeScript — common tool & retrieval packages

@langchain/core must be installed explicitly in yarn workspaces and monorepos — it is a peer dependency and will not always be hoisted automatically.

Minimal Project Templates

Add your model provider, e.g.:

langchain-openai

langchain-anthropic

langchain-google-genai

</python>
</ex-langgraph-python>

<ex-langgraph-typescript>
<typescript>
Minimal package.json dependencies for a LangGraph project (provider-agnostic).
```json
{
  "dependencies": {
    "@langchain/core": "^1.0.0",
    "langchain": "^1.0.0",
    "@langchain/langgraph": "^1.0.0",
    "langsmith": "^0.3.0"
  }
}

Add your model provider, e.g.:

langchain-anthropic

langchain-openai

</python>
</ex-deepagents-python>

<ex-deepagents-typescript>
<typescript>
Minimal package.json dependencies for a Deep Agents project (provider-agnostic).
```json
{
  "dependencies": {
    "deepagents": "latest",
    "@langchain/core": "^1.0.0",
    "langchain": "^1.0.0",
    "langsmith": "^0.3.0"
  }
}

Web search

langchain-tavily # use latest; partner package, semver

Vector store — pick one:

langchain-chroma # use latest; partner package, semver

langchain-pinecone # use latest; partner package, semver

langchain-qdrant # use latest; partner package, semver

Text processing

langchain-text-splitters # use latest; semver

Your model provider:

langchain-openai / langchain-anthropic / etc.

</python>
</ex-with-tools-python>

<ex-with-tools-typescript>
<typescript>
Adding Tavily search and a vector store to a LangGraph project.
```json
{
  "dependencies": {
    "@langchain/core": "^1.0.0",
    "langchain": "^1.0.0",
    "@langchain/langgraph": "^1.0.0",
    "langsmith": "^0.3.0",
    "@langchain/tavily": "latest",
    "@langchain/pinecone": "latest"
  }
}

Environment Variables

# LangSmith (always recommended for observability)
LANGSMITH_API_KEY=<your-key>
LANGSMITH_PROJECT=<project-name>   # optional, defaults to "default"

# Model provider — set the one(s) you use
OPENAI_API_KEY=<your-key>
ANTHROPIC_API_KEY=<your-key>
GOOGLE_API_KEY=<your-key>
MISTRAL_API_KEY=<your-key>
GROQ_API_KEY=<your-key>
COHERE_API_KEY=<your-key>
FIREWORKS_API_KEY=<your-key>
TOGETHER_API_KEY=<your-key>
HUGGINGFACEHUB_API_TOKEN=<your-key>

# Common tool/retrieval services
TAVILY_API_KEY=<your-key>          # for Tavily search
PINECONE_API_KEY=<your-key>        # for Pinecone

Environment Requirements

Versioning Policy & Upgrade Strategy

Breaking changes only happen in major versions (1.x → 2.x) for all semver-compliant packages. Deprecated features remain functional across the entire 1.x series with warnings.

Prefer dedicated integration packages over langchain-community. When a dedicated package exists (e.g. langchain-chroma instead of langchain-community's Chroma integration), use it — dedicated packages are independently versioned and better tested.

Community tool packages (Tavily, vector stores, etc.) should be kept at latest unless your project requires a locked environment. These packages frequently release compatibility fixes alongside LangChain/LangGraph updates.

Common Mistakes

CORRECT: LangChain 1.0 LTS

langchain>=1.0,<2.0

</fix-legacy-version>

<fix-community-unpinned>
`langchain-community` can break on minor version bumps — it does not follow semver.

WRONG: allows minor-version updates that may be breaking

langchain-community>=0.4

CORRECT: pin to exact minor series

langchain-community>=0.4.0,<0.5.0

Also consider switching to the equivalent dedicated integration package if one exists (e.g. `langchain-chroma` instead of the community Chroma integration).
</fix-community-unpinned>

<fix-community-tool-outdated>
Community tool packages like `langchain-tavily` and vector store integrations release compatibility fixes alongside LangChain updates. Using an old pinned version can cause import errors or broken tool schemas.

RISKY: old pin may be incompatible with LangChain 1.0

langchain-tavily==0.0.1

BETTER: allow latest within the current major

langchain-tavily>=0.1

</fix-community-tool-outdated>

<fix-community-import-deprecated>
Many tools that used to live in `langchain-community` now have dedicated packages with updated import paths. Always prefer the dedicated package import.

```python
# WRONG — deprecated community import path
from langchain_community.tools.tavily_search import TavilySearchResults
from langchain_community.tools import WikipediaQueryRun
from langchain_community.vectorstores import Chroma
from langchain_community.vectorstores import Pinecone

# CORRECT — use dedicated package imports
from langchain_tavily import TavilySearch                  # pip: langchain-tavily (TavilySearchResults is deprecated)
from langchain_community.tools import WikipediaQueryRun  # no dedicated pkg yet
from langchain_chroma import Chroma                       # pip: langchain-chroma
from langchain_pinecone import PineconeVectorStore        # pip: langchain-pinecone

To find the current canonical import for any integration, search the integrations directory: https://python.langchain.com/docs/integrations/tools/

Each entry shows the correct package and import path. If a dedicated package exists, use it — the community path may still work but is considered legacy. </fix-community-import-deprecated>

// CORRECT: always list @langchain/core explicitly { "dependencies": { "@langchain/core": "^1.0.0", "@langchain/langgraph": "^1.0.0" } }

</typescript>
</fix-core-not-installed>

<fix-python-version>
<python>
Python 3.9 and below are not supported by LangChain 1.0.
```python
# Verify before installing
import sys
assert sys.version_info >= (3, 10), "Python 3.10+ required for LangChain 1.0"