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](#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/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
# 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 PineconeCommon 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,<0.5.0Also 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-pineconeTo 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