Offered By: IBMSkillsNetwork
Build Smarter AI Apps: Empower LLMs with LangChain
Learn hands-on with LangChain and master its concepts through practical applications—from models and prompts to conversational memory, tools and agents. LangChain is an essential tool for developers and data scientists who work with large language models, this open-source framework empowers LLM development with flexible tools and abstractions for integration with data sources and workflows. Perfect for those looking to streamline Gen AI development and improve application relevance with exercises designed to enhance your skills in LLM interactions, document parsing, and agent-based querying.
Continue readingGuided Project
Artificial Intelligence
At a Glance
Learn hands-on with LangChain and master its concepts through practical applications—from models and prompts to conversational memory, tools and agents. LangChain is an essential tool for developers and data scientists who work with large language models, this open-source framework empowers LLM development with flexible tools and abstractions for integration with data sources and workflows. Perfect for those looking to streamline Gen AI development and improve application relevance with exercises designed to enhance your skills in LLM interactions, document parsing, and agent-based querying.
Why this topic is important
LangChain is quickly becoming an essential tool for developers and data scientists who work with large language models (LLMs). As LLMs continue to grow in popularity, so does the demand for ways to integrate them effectively into real-world applications. LangChain's modular, open-source framework allows users to harness the power of LLMs by connecting them to various data sources and customizing outputs for specific workflows. By mastering LangChain, you can streamline LLM development, reduce time spent on fine-tuning, and enhance the adaptability and relevance of AI models. Completing this project will equip you with practical skills to take full advantage of LangChain’s robust framework and optimize your AI-driven applications.
A look at the project ahead
In this hands-on project, you’ll dive into the fundamentals of LangChain and explore how to leverage its key components to build smarter, more adaptable LLM applications. You will mostly use mixtral-8x7b-instruct-v01 model hosted by watsonx.ai. Here’s what you’ll learn and accomplish:
- Understand and implement LangChain's core concepts, including models, prompts, agents, and tools. You’ll learn how each component can be used to customize and streamline interactions with LLMs.
- Apply LangChain’s module-based approach to integrate LLMs with external data sources, conduct dynamic testing, and experiment with different prompts and foundation models without significant code changes. This flexibility will allow you to adapt LLM applications efficiently for specific tasks.
By the end of this project, you’ll learn the fundamentals of LangChain’s framework to enhance LLM integration, optimize model outputs, and create sophisticated applications tailored to meet diverse needs. Join us in this practical exploration of LangChain and unlock the full potential of large language models in your projects.
What you'll need
Before starting this project, ensure you have:
- A basic understanding of Python programming.
- Access to a modern web browser like Chrome, Edge, Firefox, Internet Explorer, or Safari for optimal performance.
Note that the IBM Skills Network Labs environment includes pre-installed with necessary tools to simplify your setup process.
Estimated Effort
40 Minutes
Level
Intermediate
Skills You Will Learn
Artificial Intelligence, Generative AI, LangChain, LLM, Machine Learning
Language
English
Course Code
GPXX0G0DEN