Learning LangChain empowers you to seamlessly integrate advanced language models like GPT-4 into diverse applications, unlocking capabilities in natural language processing and AI-driven applications.
We just published a full course on the freeCodeCamp.org YouTube channel that will teach you how to build six end-to-end projects using LangChain and a variety of LLMs. Krish Naik created this course. He is a popular instructor with over 800,000 subscribers on his YouTube channel.
In this course you will learn to use LangChain with GPT-4, Google Gemini Pro, and Llama 2, creating a suite of practical, real-world applications.
- LangChain: This tool helps integrate various Large Language Models (LLMs) like OpenAI’s GPT-3.5 and GPT-4 with external data sources. It opens up a world where the processing of natural language goes beyond pre-fed data, allowing for more dynamic and contextually aware applications.
- GPT-4: This is the latest LLM from OpenAI. This course will demonstrate how GPT-4’s advanced capabilities can be harnessed in tandem with LangChain for creating sophisticated Natural Language Processing (NLP) applications.
- Google Gemini Pro: This component provides an in-depth look at Google’s powerful tool for language understanding and processing, demonstrating its application in real-time scenarios.
- Llama 2: Focused on blog generation and other content creation, Llama 2 represents the forefront of language model technology. It offers insights into how these models can be utilized for creative and efficient content generation.
Introduction: What We Will Learn
In this introductory section, learners are acquainted with the course structure and the key objectives. It sets the stage for an immersive learning experience, outlining how each technology – LangChain, GPT-4, Google Gemini Pro, and Llama 2 – will be explored and integrated. This section emphasizes the importance of these technologies in the realm of NLP and sets expectations for the skills and knowledge to be gained.
LangChain Crash Course
This segment offers a comprehensive introduction to LangChain, a framework designed to connect powerful Large Language Models (LLMs) like GPT-3.5 and GPT-4 with various external data sources. It covers the basics of LangChain’s functionality, how it enables the building of more versatile NLP applications, and its role in enhancing the capabilities of LLMs. This course module is crucial for understanding the foundation upon which the subsequent projects are built.
Chat With PDF Using Langchain And Astradb
Here, learners will dive into a practical application of LangChain by creating a chat interface that can interact with PDF documents. This project involves integrating Astradb, a database solution, with LangChain, demonstrating how to extract and process information from PDFs. This section highlights the utility of LangChain in real-world scenarios, such as data retrieval and information management.
Blog Generation Using Llama 2 LLM Models
This part of the course focuses on Llama 2, a language model adept at generating human-like text. Participants will learn how to harness Llama 2 for automated blog content creation. This module not only explores the capabilities of Llama 2 in generating coherent and contextually relevant text but also delves into the nuances of fine-tuning language models for specific content styles and themes.
End To End LLm Projects Using Pinecone VectorDB
In this section, the course explores the integration of LLMs with Pinecone VectorDB, a database engineered for vector search and storage. This section teaches how to build end-to-end NLP projects that leverage the strengths of both LLMs and VectorDB for efficient data handling and retrieval. It’s a deep dive into creating scalable, AI-driven applications with advanced search capabilities.
Google Gemini Pro Demo
This segment provides an in-depth look at Google Gemini Pro, showcasing its advanced features for language understanding and processing. Through a series of demonstrations, learners will see how Gemini Pro can be applied in various scenarios, emphasizing its role in enhancing the quality and efficiency of NLP tasks. This practical demonstration underlines the power and flexibility of Gemini Pro in handling complex language processing challenges.
Focusing on the practical application of LLMs in business contexts, this section guides learners through creating a multi-language invoice extractor. This project highlights the use of LLMs in processing and extracting key information from invoices in various languages, showcasing the technology’s versatility and applicability in global business operations.
Conversational Q&A Chatbot Using Gemini Pro API
The final section of the course is dedicated to building a sophisticated conversational Q&A chatbot using the Gemini Pro API. This project encapsulates the learnings from the entire course, applying them to create an interactive chatbot capable of handling nuanced conversations. This section not only reinforces the learners’ understanding of Gemini Pro’s capabilities but also illustrates the practicalities of deploying AI-driven conversational agents in real-world scenarios.
Each section of the course is designed to build upon the previous ones, ensuring a comprehensive and cohesive learning experience that equips participants with both theoretical knowledge and practical skills in the latest NLP technologies.
This is a great course to understand how LangChain can work with a variety of technologies. Watch the full course on the freeCodeCamp.org youTube channel (4-hour watch).