Langchain Integration

​

Introduction

Langchain is a Python and Node.js framework to build applications on top of large-language models (OpenAI, Llama, Gemini).

Building on top of LLMs comes with many challenges:

• Gathering and preparing the data (context) and providing memory to models
• Orchestrating tasks to match LLM API requirements (ex, rate limiting, chunking)
• Parse the different LLM result format

Langchain comes with a set of high-level concepts and tools to cope with those challenges:

• Retrieval modules such as Document Loaders or Text splitter help with gathering and preparing the data provided to the models
• Model I/O is a set of tools that help to normalize the APIs across multiple models (ex: Prompt Templates)
• Agents and Tools help to build reasoning (ex: how to answer based on provided context, what actions to take)
• Chains help in orchestrating all the above

Browserbase provides a Document Loader to enable your Langchain application to browse the web to:

• Extract text or raw HTML, including from web pages using JavaScript or dynamically rendered text
• Load images via screenshots

​

Add Browserbase to your Langchain application

To get started, proceed to the Node.js or Python guides to learn more about using Browserbase with Langchain.