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Offered By: IBMSkillsNetwork

Create AI powered apps with open source LangChain

Discover LangChain, a dynamic Python library for large language models (LLMs). Seamlessly integrate with models from OpenAI, Cohere, Huggingface Hub, IBM Watsonx, Azure OpenAI, and more. Handle diverse document formats, extract data with ease, and create engaging, human-like dialogues. Ideal for developers creating conversational AI and data scientists extracting information from various documents. Furthermore, you will also learn how to use Docker container to deploy your AI app into IBM Code Engine which everyone can access over the internet.

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Guided Project

Artificial Intelligence

148 Enrolled
4.5
(140 Reviews)

At a Glance

Discover LangChain, a dynamic Python library for large language models (LLMs). Seamlessly integrate with models from OpenAI, Cohere, Huggingface Hub, IBM Watsonx, Azure OpenAI, and more. Handle diverse document formats, extract data with ease, and create engaging, human-like dialogues. Ideal for developers creating conversational AI and data scientists extracting information from various documents. Furthermore, you will also learn how to use Docker container to deploy your AI app into IBM Code Engine which everyone can access over the internet.

Discover LangChain, a revolutionary Python library that serves as your portal to the world of large language models (LLMs). LangChain is your one-stop solution for integrating with a wide range of LLMs from industry leaders such as OpenAI, Cohere, Huggingface Hub, IBM Watsonx, Azure OpenAI, and more.

But LangChain is more than just a bridge to these models. It's a versatile tool that empowers you to handle and process information from a diverse range of document formats, from text and HTML to PDF and PowerPoint, and even emails. With LangChain, data extraction is as easy as a few lines of code, making it your Swiss Army knife for information processing.

The power of LangChain doesn't stop there. It also provides you with the tools to create engaging, interactive dialogues with language models. With its innovative conversation chains and agents, LangChain allows you to design human-like conversations that blur the line between man and machine. Combined with memory and prompt templates, you can create dialogues that are not only engaging but also intelligent.

Whether you're a developer aiming to create a conversational AI, or a data scientist looking to extract information from a myriad of document formats, LangChain is the Python library that brings your language processing tasks to life.

In final step, we will show you step-by-step how to use Docker container and  IBM Code Engine to deploy your AI application on IBM Cloud. IBM Code Engine is a fully managed, serverless platform that provides an abstraction for the underlying infrastructure required to deploy your apps and lets you focus on the source code only (such as the Python code). longdescriptionimage.png 663 KB

A Look at the Project Ahead

You will following Langchain functionalities:
  1. Universal Interface: LangChain provides seamless integration with various LLM models, making it easier than ever to leverage the power of these models in your applications.
  2. Prompt Management: With LangChain, you can easily handle, optimize, and serialize prompts, making your interactions with LLMs more efficient and effective.
  3. Conversation Chains: LangChain enables you to create complex dialogues with LLMs, allowing for more engaging and interactive conversations.
  4. Memory Interface: LangChain facilitates the storing and retrieving of model information, making it easier to manage and utilize your models.
  5. Indexes: LangChain provides utility functions for loading custom text data, giving you more flexibility in how you use your models.
  6. Agents and Tools: With LangChain, you can set up agents that can use tools like Google Search, Wikipedia, or a calculator, adding more functionality to your applications.
You will also learn:
  1. Get familiar with Docker container and learn how to create the container image for App Deployment
  2. Deploy your app using IBM Code Engine
Join us on this exciting journey and unlock the potential of language processing with LangChain.


What You'll Need

The scripts in this guided project are set up to send a request to the OpenAI API using the LangChain library, are you are required to insert your OpenAI API key.
To get an OpenAI API key for ChatGPT, you can follow these steps:
1. Visit OpenAI’s official website on your preferred browser (https://platform.openai.com/).
2. Click on “Log-In” and add your email to create an account.
3. Once logged in, click on the “View API Keys” icon located in the top-right corner of the screen.
4. Click on “Create an API Key” to generate your ChatGPT API Key.

As of June 2023, new free trial users receive $5 (USD) worth of credit which expires after three months.

Certificate

Certificate Offered

Estimated Effort

2 Hours

Level

Intermediate

Industries

Information Technology

Skills You Will Learn

Artificial Intelligence, Chatbots, Embeddable AI, Generative AI, LLM, Python

Language

English

Course Code

GPXX0W2REN

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