How to Intermediate · 3 min read

How to migrate LangChain ConversationChain to LCEL

Q: How to migrate LangChain ConversationChain to LCEL

To migrate from ConversationChain to LCEL, replace the old chain initialization with LCEL constructs using the new prompt templates and chat models. Use langchain_core and langchain_openai imports, and adapt your message handling to the LCEL API patterns.

Quick answer

To migrate from ConversationChain to LCEL, replace the old chain initialization with LCEL constructs using the new prompt templates and chat models. Use langchain_core and langchain_openai imports, and adapt your message handling to the LCEL API patterns.

PREREQUISITES

Python 3.8+
OpenAI API key (free tier works)
pip install langchain_openai langchain_core

Setup

Install the required LangChain packages and set your OpenAI API key in the environment.

bash

pip install langchain_openai langchain_core

Step by step

This example shows how to migrate a simple ConversationChain to LCEL using ChatOpenAI and ChatPromptTemplate.

python

import os
from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate

# Old ConversationChain style (for reference):
# from langchain.chains import ConversationChain
# llm = ChatOpenAI(model_name="gpt-4o", temperature=0)
# chain = ConversationChain(llm=llm)
# response = chain.run("Hello, how are you?")

# New LCEL style migration:

# Initialize the chat model
chat = ChatOpenAI(model_name="gpt-4o", temperature=0, openai_api_key=os.environ["OPENAI_API_KEY"])

# Define a prompt template
prompt = ChatPromptTemplate.from_messages([
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "{input}"}
])

# Compose the chain
from langchain_core.chains import LLMChain

chain = LLMChain(llm=chat, prompt=prompt)

# Run the chain
response = chain.invoke({"input": "Hello, how are you?"})
print(response["text"])

output

I'm doing well, thank you! How can I assist you today?

Common variations

You can use async calls with await chain.ainvoke() or switch to other models like gpt-4o-mini. For Anthropic models, use ChatAnthropic with similar prompt templates.

python

import asyncio

async def async_example():
    response = await chain.ainvoke({"input": "Hello asynchronously!"})
    print(response["text"])

asyncio.run(async_example())

output

Hello asynchronously! How can I help you today?

Troubleshooting

If you see ImportError, verify you installed langchain_openai and langchain_core.
If the API key is missing, set OPENAI_API_KEY in your environment.
For prompt errors, ensure your prompt template matches the new LCEL format.

✅

Key Takeaways

Use ChatOpenAI and ChatPromptTemplate from langchain_openai and langchain_core to migrate to LCEL.
Replace ConversationChain with LLMChain and adapt your prompt structure accordingly.
Use chain.invoke() for synchronous calls and chain.ainvoke() for async.
Always load your API key from os.environ to avoid hardcoding.
Check your prompt roles and formatting to match LCEL expectations.

Verified 2026-04 · gpt-4o, gpt-4o-mini

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