---

name: langchain-upgrade-migration description: | Plan and execute LangChain SDK upgrades and migrations. Use when upgrading LangChain versions, migrating from legacy patterns, or updating to new APIs after breaking changes. Trigger with phrases like "upgrade langchain", "langchain migration", "langchain breaking changes", "update langchain version", "langchain 0.3". allowed-tools: Read, Write, Edit, Bash(pip:*), Grep version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io

LangChain Upgrade Migration

Overview

Guide for upgrading LangChain versions safely with migration strategies for breaking changes.

Prerequisites

• Existing LangChain application
• Version control with current code committed
• Test suite covering core functionality
• Staging environment for validation

Instructions

Step 1: Check Current Versions

Copypip show langchain langchain-core langchain-openai langchain-community

# Output current requirements
pip freeze | grep -i langchain > langchain_current.txt

Step 2: Review Breaking Changes

Copy# Key breaking changes by version:

# 0.1.x -> 0.2.x (Major restructuring)
# - langchain-core extracted as separate package
# - Imports changed from langchain.* to langchain_core.*
# - ChatModels moved to provider packages

# 0.2.x -> 0.3.x (LCEL standardization)
# - Legacy chains deprecated
# - AgentExecutor changes
# - Memory API updates

# Check migration guides:
# https://python.langchain.com/docs/versions/migrating_chains/

Step 3: Update Import Paths

Copy# OLD (pre-0.2):
from langchain.chat_models import ChatOpenAI
from langchain.prompts import ChatPromptTemplate
from langchain.chains import LLMChain

# NEW (0.3+):
from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser

# Migration script
import re

def migrate_imports(content: str) -> str:
    """Migrate old imports to new pattern."""
    migrations = [
        (r"from langchain\.chat_models import ChatOpenAI",
         "from langchain_openai import ChatOpenAI"),
        (r"from langchain\.llms import OpenAI",
         "from langchain_openai import OpenAI"),
        (r"from langchain\.prompts import",
         "from langchain_core.prompts import"),
        (r"from langchain\.schema import",
         "from langchain_core.messages import"),
        (r"from langchain\.callbacks import",
         "from langchain_core.callbacks import"),
    ]
    for old, new in migrations:
        content = re.sub(old, new, content)
    return content

Step 4: Migrate Legacy Chains to LCEL

Copy# OLD: LLMChain (deprecated)
from langchain.chains import LLMChain

chain = LLMChain(llm=llm, prompt=prompt)
result = chain.run(input="hello")

# NEW: LCEL (LangChain Expression Language)
from langchain_core.output_parsers import StrOutputParser

chain = prompt | llm | StrOutputParser()
result = chain.invoke({"input": "hello"})

Step 5: Migrate Agents

Copy# OLD: initialize_agent (deprecated)
from langchain.agents import initialize_agent, AgentType

agent = initialize_agent(
    tools=tools,
    llm=llm,
    agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION
)

# NEW: create_tool_calling_agent
from langchain.agents import create_tool_calling_agent, AgentExecutor
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder

prompt = ChatPromptTemplate.from_messages([
    ("system", "You are a helpful assistant."),
    ("human", "{input}"),
    MessagesPlaceholder(variable_name="agent_scratchpad"),
])

agent = create_tool_calling_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools)

Step 6: Migrate Memory

Copy# OLD: ConversationBufferMemory
from langchain.memory import ConversationBufferMemory

memory = ConversationBufferMemory()
chain = LLMChain(llm=llm, prompt=prompt, memory=memory)

# NEW: RunnableWithMessageHistory
from langchain_core.chat_history import BaseChatMessageHistory
from langchain_core.runnables.history import RunnableWithMessageHistory
from langchain_community.chat_message_histories import ChatMessageHistory

store = {}

def get_session_history(session_id: str) -> BaseChatMessageHistory:
    if session_id not in store:
        store[session_id] = ChatMessageHistory()
    return store[session_id]

chain_with_history = RunnableWithMessageHistory(
    chain,
    get_session_history,
    input_messages_key="input",
    history_messages_key="history"
)

Step 7: Upgrade Packages

Copy# Create backup of current environment
pip freeze > requirements_backup.txt

# Upgrade to latest stable
pip install --upgrade langchain langchain-core langchain-openai langchain-community

# Or specific version
pip install langchain==0.3.0 langchain-core==0.3.0

# Verify versions
pip show langchain langchain-core

Step 8: Run Tests

Copy# Run test suite
pytest tests/ -v

# Check for deprecation warnings
pytest tests/ -W error::DeprecationWarning

# Run type checking
mypy src/

Migration Checklist

• Current version documented
• Breaking changes reviewed
• Imports updated
• LLMChain -> LCEL migrated
• Agent initialization updated
• Memory patterns updated
• Tests passing
• Staging validation complete

Error Handling

Resources

• LangChain Migration Guide
• LCEL Documentation
• Release Notes
• Deprecation Timeline

Next Steps

After upgrade, use langchain-common-errors to troubleshoot any issues.