What is LangChain?

LangChain is a new software library created by Harrison Chase that entered the scene around late 2022, amid a skyrocketing interest in Large Language Models (LLMs) due to significant advances in the field. Despite being in its early days, LangChain is already packed with fantastic features for building tools around the core of LLMs​. They recently announce $10M in seed funding.

What is LangChain?

LangChain is a framework built around LLMs, designed for applications such as chatbots, Generative Question-Answering (GQA), summarization, and much more. The core idea of the library is to "chain" together different components to create more advanced use cases around LLMs. Chains may consist of multiple components from several modules:

Key features of LangChain

• Standard interface for interacting with LLMs: LangChain provides a standard interface for interacting with LLMs, which makes it easy to switch between different LLMs and to build applications that are portable and easy to maintain.
• A variety of tools and libraries: LangChain provides a variety of tools and libraries to help developers build applications that are both powerful and easy to use. These tools include:
• A chain library that provides a way to combine multiple LLM calls into a single, coherent application.
• A memory library that provides a way to persist state between calls of a chain.
• An evaluation library that provides a way to measure the performance of a chain.
• A large and active community: LangChain has a large and active community of developers who are constantly contributing new features and improvements. This makes it a great choice for developers who want to be on the cutting edge of LLM technology.

How to use LangChain

To use LangChain, developers first need to install the LangChain Python library. Once the library is installed, developers can start building applications using LLMs. LangChain provides a variety of examples to help developers get started.

• ❓ Question Answering over specific documents
• 💬 Chatbots
• 🤖 Agents

Getting Started with Python

This code will create a prompt template that generates a limerick about a given topic. The user can then set the topic, and the prompt will generate a limerick. In this example, the limerick is about a cat.

import langchain

# Create a prompt template
template = """
Generate a limerick about {topic}
"""

# Create a prompt
prompt = langchain.PromptTemplate(template, input_variables=['topic'])

# Set the topic of the limerick
topic = "a cat"

# Generate the limerick
limerick = prompt.generate_answer(topic)

# Print the limerick
print(limerick)

Here is the output of the code:

There once was a cat named Mittens
Whose fur was as soft as kittens
She loved to play
And chase mice all day
And eat tuna fish with her mittens

As you can see, the code is very simple to understand and use. You can easily customize the prompt template to generate different types of text.

Conclusion

LangChain is a powerful tool that can help developers build applications using LLMs. It is a great choice for developers who want to build applications that are both powerful and easy to use.