Langchain
Langchain Integration
Add Browserbase to your Langchain application (Python).
Introduction
Langchain is a Python 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 Python guide to learn more about using Browserbase with Langchain.