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>

| Requirement | Python | TypeScript / Node |

|-------------|--------|-------------------|

| Runtime minimum | Python 3.10+ | Node.js 20+ |

| LangChain | 1.0+ (LTS) | 1.0+ (LTS) |

| LangSmith SDK | >= 0.3.0 | >= 0.3.0 |

</environment-requirements>

Framework Choice

<framework-choice>

Pick one agent orchestration layer. You do not need both.

| Framework | When to use | Core extra package |

|-----------|-------------|--------------------|

| LangGraph | Need fine-grained graph control, custom workflows, loops, or branching | langgraph / @langchain/langgraph |

| Deep Agents | Want batteries-included planning, memory, file context, and skills out of the box | deepagents (depends on LangGraph; installs it as a transitive dep) |

Both sit on top of langchain + langchain-core + langsmith.

</framework-choice>

Core Packages

<python-packages>

Python — always required

| Package | Role | Min version |

|---------|------|-------------|

| langchain | Agents, chains, retrieval | 1.0 |

| langchain-core | Base types & interfaces (peer dep) | 1.0 |

| langsmith | Tracing, evaluation, datasets | 0.3.0 |

Python — orchestration (pick one)

| Package | Use when | Min version |

|---------|----------|-------------|

| langgraph | Building custom graphs directly | 1.0 |

| deepagents | Using the Deep Agents framework | latest |

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

| Package | Provider |

|---------|----------|

| langchain-openai | OpenAI (GPT-4o, o3, …) |

| langchain-anthropic | Anthropic (Claude) |

| langchain-google-genai | Google (Gemini) |

| langchain-mistralai | Mistral |

| langchain-groq | Groq (fast inference) |

| langchain-cohere | Cohere |

| langchain-fireworks | Fireworks AI |

| langchain-together | Together AI |

| langchain-huggingface | Hugging Face Hub |

| langchain-ollama | Ollama (local models) |

| langchain-aws | AWS Bedrock |

| langchain-azure-ai | Azure AI Foundry |

Python — common tool & retrieval packages

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

| Package | Adds | Notes |

|---------|------|-------|

| langchain-tavily | Tavily web search (TavilySearch) | Dedicated integration package; prefer latest |

| langchain-text-splitters | Text chunking utilities | Semver, keep current |

| langchain-community | 1000+ integrations (fallback) | NOT semver — pin to minor series |

| faiss-cpu | FAISS vector store (local) | Via langchain-community; use latest |

| langchain-chroma | Chroma vector store | Dedicated integration package; prefer latest |

| langchain-pinecone | Pinecone vector store | Dedicated integration package; prefer latest |

| langchain-qdrant | Qdrant vector store | Dedicated integration package; prefer latest |

| langchain-weaviate | Weaviate vector store | Dedicated integration package; prefer latest |

| langsmith[pytest] | pytest plugin for LangSmith | Requires langsmith >= 0.3.4 |

> 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

| Package | Role | Min version |

|---------|------|-------------|

| @langchain/core | Base types & interfaces (peer dep) | 1.0 |

| langchain | Agents, chains, retrieval | 1.0 |

| langsmith | Tracing, evaluation, datasets | 0.3.0 |

TypeScript — orchestration (pick one)

| Package | Use when | Min version |

|---------|----------|-------------|

| @langchain/langgraph | Building custom graphs directly | 1.0 |

| deepagents | Using the Deep Agents framework | latest |

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

| Package | Provider |

|---------|----------|

| @langchain/openai | OpenAI (GPT-4o, o3, …) |

| @langchain/anthropic | Anthropic (Claude) |

| @langchain/google-genai | Google (Gemini) |

| @langchain/mistralai | Mistral |

| @langchain/groq | Groq (fast inference) |

| @langchain/cohere | Cohere |

| @langchain/aws | AWS Bedrock |

| @langchain/azure-openai | Azure OpenAI |

| @langchain/ollama | Ollama (local models) |

TypeScript — common tool & retrieval packages

| Package | Adds | Notes |

|---------|------|-------|

| @langchain/tavily | Tavily web search (TavilySearch) | Dedicated integration package; prefer latest |

| @langchain/community | Broad set of community integrations | Use sparingly; prefer dedicated packages |

| @langchain/pinecone | Pinecone vector store | Dedicated integration package; prefer latest |

| @langchain/qdrant | Qdrant vector store | Dedicated integration package; prefer latest |

| @langchain/weaviate | Weaviate vector store | Dedicated integration package; prefer latest |

> @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
# 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.

{
  "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"
  }
}

</typescript>

</ex-with-tools-typescript>

Versioning Policy & Upgrade Strategy

<versioning-policy>

| Package group | Versioning | Safe upgrade strategy |

|---------------|------------|-----------------------|

| langchain, langchain-core | Strict semver (1.0 LTS) | Allow minor: >=1.0,<2.0 |

| langgraph / @langchain/langgraph | Strict semver (v1 LTS) | Allow minor: >=1.0,<2.0 |

| langsmith | Strict semver | Allow minor: >=0.3.0 |

| Dedicated integration packages (e.g. langchain-tavily, langchain-chroma) | Independently versioned | Allow minor updates; use latest |

| langchain-community | NOT semver | Pin exact minor: >=0.4.0,<0.5.0 |

| deepagents | Follow project releases | Pin to tested version in production |

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.

</versioning-policy>

Environment Variables

<environment-variables>

All keys are read from the environment at runtime. Set only the keys for services you actually use.

# 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-variables>

Common Mistakes

<fix-legacy-version>

Never start a new project on LangChain 0.3. It is maintenance-only until December 2026.

# WRONG: legacy, no new features, security patches only
langchain>=0.3,<0.4

# 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.

# 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>

<fix-core-not-installed>

<typescript>

@langchain/core is a peer dependency — it must be in your package.json, especially in monorepos.

// WRONG: missing @langchain/core (breaks in yarn workspaces / strict hoisting)
{
  "dependencies": {
    "@langchain/langgraph": "^1.0.0"
  }
}

// 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.

# Verify before installing
import sys
assert sys.version_info >= (3, 10), "Python 3.10+ required for LangChain 1.0"

</python>

</fix-python-version>

<fix-node-version>

<typescript>

Node.js below 20 is not officially supported.

# Verify before installing
node --version   # must be v20.x or higher

</typescript>

</fix-node-version>