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GenAI: Function Calling, Whisper, LangChain (UPDATED 2024)

Name: GenAI: Function Calling, Whisper, LangChain (UPDATED 2024)
Rating: 4.4 (44 reviews)

Hands-on projects (JS & Python) to get started fast with Conversational AI, Speech-to-text, Function calling & LangChain

Created bySandra L. Sorel

Last updated 12/2024

English

What you'll learn

OpenAI API : learn to interact with the language models and integrate AI into web projects (Javascript and Python)
By the end of the course, students will be able to integrate GPT models into various applications, including chatbots and content generators.
Chat Completions API : learn to set up and integrate the Chat Completions API into existing projects
Function Calling : extend the Large Languages models (LLMs)'s capacities with the ability to call external APIs
Speech-to-Text (Whisper Audio) : set up a simple use-case in Python to turn audio files into transcripts
Langchain : to simplify the creation of applications using Large Languages models (LLMs)
[PROJECT] (Python) : quickstart example to integrate an intelligence layer into a web project
[PROJECT] (Nodejs) : Create a customized Chatbot with the Chat language models
[PROJECT] (Python) : convert audio podcast samples to text with the Whisper Audio API
[PROJECT] (LangChain Javascript) : Build a transcriber and summarizer app with the OpenAI LLMs, Whisper Audio API and the Summarization Chain

Course content

8 sections • 46 lectures • 2h 27m total length

Welcome1:22
Exercise Files (download)2:38
Access downloadable exercise files, code samples, and APIs to build chat bots, transcribe audio with Whisper, and fetch weather data via a function calling OpenWeatherMap integration—using FastAPI and GPT models.
Download the Exercise Files0:01

Getting Started with OpenAI : First Look1:21
Download the starter project1:56
Download the starter project for factual answering, run a command-line interface to ask AI factual questions, and configure OpenAI API keys and language models to generate completions.
Requirements & Set up the development environment0:05
Setting up the environment (Quickstart guide)4:48
Setting up an API Key6:12
Configure your project with an API key to interact with the language model, set up environment variables, and run a test prompt using Python with the legacy completions API.
Defining environment variables
Making API Requests9:33

Introduction & Learning Objectives0:15
Setting up a Node server with Express4:41
Express server : {source code}0:07
Defining Prompts and making requests5:46
Define prompts and send requests to a language model via a post route in a rest api, configure api keys, system messages, and json handling, then test with curl.
Defining a request : { source code }0:24
Testing with Postman2:30
Test a RESTful API with postman by sending a post request to the ask route on port 5000 and validate chatbot's response, planning a UI for AI chat bots.

Introducing Function Calling5:25
Learn to enable a language model to call external APIs via function calling, using a chat endpoint and json prompts to fetch current weather data.
Getting started : starter project & Function Calling feature5:34
Kick off a starter project by defining a function and letting the language model auto call it to fetch weather data from an external API using user messages.
Calling External Data : introduction to OpenWeathermap.org12:29
Learn to fetch current weather from openweathermap.org using latitude, longitude, and an API key, including geocoding to coordinates and converting Kelvin to Celsius or Fahrenheit.
Source code to fetch the current weather information0:27
Testing Function Calling6:54
Final steps - connect to the chatbot3:11
Build a full-stack chatbot that uses function calling to fetch current weather data from an external API and display it within a natural chat conversation.
2024 UPDATE - Python Example (Google Colab)0:06

Getting started : Langchain, Audio Whisper ...3:41
Download starter Project & install dependencies3:56
Audio whisper model : install loader6:04
Building a transcription application : Summarization chain5:25
Build a transcription application by running a summarization chain over transcripts using a wrapper OpenAI model, loader, and text splitter, converting transcripts into documents and generating concise summaries.
Testing with Postman1:43
Build a React client application2:00
Connect and run a React client app, install dependencies with npm i, start the server, and perform transcription and summarization via Axios, displaying the transcript and summary.
Final steps6:03

Requirements

Basics of programming language and web development : HTML & CSS
Javascript fundamentals + knowledge of ECMAScript 2015
Basic Python programming
Basic Online Editor or IDE (recommanded : Visual studio code)
Basic command line operations
Modern Browser (Chrome, Safari, Brave) and the React Developer Tools

Description

- The OpenAI API is one of the most exciting advancements in the world of natural language and code processing.

- Its powerful models and flexible endpoints offer a wealth of possibilities for web developers looking to take their skills to the next level.

- In this course, you'll dive into the world of OpenAI APIs and GPT language models. Our focus will be on the completions endpoint and how it can be applied to text completion and various other language-processing tasks.

- Students will work on an end-to-end Generative AI project incorporating the learned concepts.

The course includes Projects, Hands-on Labs, Case Studies and Real-world Applications.

# 1: Introduction to Generative AI :

with the OpenAI API to solve a wide range of language processing tasks, including :
- content generation, summarization, semantic search, and sentiment analysis

a quickstart Tutorial to gain experience and build your first AI-powered application with the APIs and the large language models (LLMs).
- You will learn how to build a simple sample node application.
- Along the way, you’ll learn key concepts and techniques :
  - authentication with the API key,
  - prompt design, adjust settings and generate completions

# 2: The Chat models Models:

explore the different language models available through the OpenAI API, including the cutting-edge GPT language model

integrate the Chat completion API to create an AI-agent

# 3: Speech-to-Text

discover the Audio Whisper API to turn audio files into transcriptions
implementing Speech-to-Text to convert podcast audio samples into text

# 4: Function Calling in AI Systems

extend the LLMs capacities
and give the language models the ability to call external APIs and generate extended responses.

# 5: Experiment with LangChain : a framework to easily create applications with the generative models

# Target and intended audience

Whether you're a seasoned web developer with years of experience or just starting, this course is designed to help you take your skills to the next level.

For Web Developers of All Levels
Basics of Node JS, ReactJS, and Python
No prior programming experience is required, and the course is suitable for developers of all levels, from beginners to advanced.

# Requirements and prerequisites for the course :

Basics of web development: HTML, CSS
Some basic programming language
The javascript fundamentals and Python

In this comprehensive course, you will gain a deep understanding of the OpenAI API and its capabilities, along with hands-on experience in building your applications using Node.js, ReactJS, and Python.

So why wait? Enroll now and unleash the full potential of AI and build your first nextGen application.

Who this course is for:

Javascript developers
Front and backend developers
Students in Web development and software engineering
Anyone interested in building apps with the OpenAI API and the AI generative models

GenAI: Function Calling, Whisper, LangChain (UPDATED 2024)

What you'll learn

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Course content

Introduction3 lectures • 4min

GPT models : integrating AI into web projects (Python Quickstart)7 lectures • 24min

Introduction to the ChatGPT AI and the Chat language models (NodeJS)6 lectures • 14min

Build a REST API (NodeJS & ExpressJS)6 lectures • 14min

Build a REST API : connect a React client application5 lectures • 15min

Extend the GPT models capacities with Function Calling (Node.js)7 lectures • 34min

Speech-2-Text (Whisper Audio API): convert audio to text (Python)5 lectures • 14min

LangChain Framework : chain and combine LLM's capabilities (Javascript)7 lectures • 29min

Requirements

Description

Who this course is for: