Langchain Dependencies

<overview> The LangChain ecosystem is split into focused, independently-versioned packages. Understanding which packages you need — and their version constraints — prevents incompatibilities and keeps upgrades predictable.

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>

Environment Requirements

<environment-requirements>

</environment-requirements>

Framework Choice

<framework-choice> Pick one agent orchestration layer. You do not need both.

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

Core Packages

<python-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.

</python-packages>

<typescript-packages>

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.

</typescript-packages>

Minimal Project Templates

<ex-langgraph-python> <python> Minimal dependency set for a LangGraph project (provider-agnostic).

# requirements.txt
langchain>=1.0,<2.0
langchain-core>=1.0,<2.0
langgraph>=1.0,<2.0
langsmith>=0.3.0

# 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).

{
  "dependencies": {
    "@langchain/core": "^1.0.0",
    "langchain": "^1.0.0",
    "@langchain/langgraph": "^1.0.0",
    "langsmith": "^0.3.0"
  }
}

</typescript> </ex-langgraph-typescript>

<ex-deepagents-python> <python> Minimal dependency set for a Deep Agents project (provider-agnostic).

# requirements.txt
deepagents            # bundles langgraph internally
langchain>=1.0,<2.0
langchain-core>=1.0,<2.0
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).

{
  "dependencies": {
    "deepagents": "latest",
    "@langchain/core": "^1.0.0",
    "langchain": "^1.0.0",
    "langsmith": "^0.3.0"
  }
}

</typescript> </ex-deepagents-typescript>

<ex-with-tools-python> <python> Adding Tavily search and a vector store to a LangGraph project.

# requirements.txt
langchain>=1.0,<2.0
langchain-core>=1.0,<2.0
langgraph>=1.0,<2.0
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