langchain-dependencies
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.
SKILL.md
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.
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 |
Framework Choice
| 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.
Core 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.
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/coremust be installed explicitly in yarn workspaces and monorepos — it is a peer dependency and will not always be hoisted automatically.
Minimal Project Templates
# 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
{
"dependencies": {
"@langchain/core": "^1.0.0",
"langchain": "^1.0.0",
"@langchain/langgraph": "^1.0.0",
"langsmith": "^0.3.0"
}
}
# 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
{
"dependencies": {
"deepagents": "latest",
"@langchain/core": "^1.0.0",
"langchain": "^1.0.0",
"langsmith": "^0.3.0"
}
}
# 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.
{
"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"
}
}
Versioning Policy & Upgrade Strategy
| 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.
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
Common Mistakes
# WRONG: legacy, no new features, security patches only
langchain>=0.3,<0.4
# CORRECT: LangChain 1.0 LTS
langchain>=1.0,<2.0
# 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).
# 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
# 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.
// 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"
}
}
# Verify before installing
import sys
assert sys.version_info >= (3, 10), "Python 3.10+ required for LangChain 1.0"
# Verify before installing
node --version # must be v20.x or higher