OpenAI Python API Startup: ChatGPT, Image Gen, Speech-Text+

Name: OpenAI Python API Startup: ChatGPT, Image Gen, Speech-Text+
Rating: 4.5 (39 reviews)

Master OpenAI's versatile API by conducting sentiment analysis, creating an AI app, customer service chatbot, and more!

Created byTal Minks

Last updated 11/2023

English

English [Auto],

What you'll learn

Master the OpenAI API
Use DallE API to generate, edit, and produce variations of images.
Fine-Tune GPT for customer service, sentiment analysis, and email organization
Use Speech to Text API to transcribe and translate audio in different languages.
Develop Python app integrating OpenAI's capabilities

Course content

8 sections • 42 lectures • 2h 51m total length

Course Curriculum0:47
Explore a structured course curriculum that blends overview and project chunks, teaching model integration, Python lessons, and final app projects using OpenAI's capabilities.
OpenAI Overview3:58
Course Materials0:20
Signing Up For an Account1:10
OpenAI Model and API Overview2:52
Model Pricing1:08
Install Pycharm1:10
Installing Latest Python and PIP0:54
Install the latest Python and pip by downloading Python and running installer, then open file settings, click the plus symbol, type pip, and install packages like pi audio and wav.
Hiding API Key2:01
Grab a unique OpenAI api key and hide it from your project repository by storing it in a separate credentials file and importing it as creds.api.

Text Generation3:55
It looks like OpenAI changed their chat completion calls.
You will now need to make sure the class OpenAI is imported like this:

from openai import OpenAI

and you will need to create an object based on the OpenAI Class like this:

client = OpenAI()
client.completions.create(model='gpt-3.5-turbo-instruct')

You will also need to change you model to this: model="gpt-3.5-turbo-instruct", as gpt 3 is deprecated.
Chat Completion Endpoint3:00
It looks like OpenAI changed their chat completion calls.
You will now need to make sure the class OpenAI is imported like this:

from openai import OpenAI

and you will need to create an object based on the OpenAI Class like this:

client = OpenAI()
client.completions.create(model='gpt-3.5-turbo-instruct')

You will also need to change you model to this: model="gpt-3.5-turbo-instruct", as gpt 3 is deprecated.
Customer Service Chatbot Intro0:57
Data Preparation3:38
Fine Tuning call format has changed. You will now need to use this with gpt 3.5:

from openai import OpenAI
client = OpenAI()

client.fine_tuning.jobs.create(
training_file="you_training_file",
model="gpt-3.5-turbo"
)
Fine-Tuning Our Chatbot Model3:56
Fine Tuning call format has changed. You will now need to use this with gpt 3.5:

from openai import OpenAI
client = OpenAI()

client.fine_tuning.jobs.create(
training_file="you_training_file",
model="gpt-3.5-turbo"
)
Troubleshooting Fine-Tuning (extra-footage)1:11
Fine Tuning call format has changed. You will now need to use this with gpt 3.5:

from openai import OpenAI
client = OpenAI()

client.fine_tuning.jobs.create(
training_file="you_training_file",
model="gpt-3.5-turbo"
)

Email Organizer Intro0:16
Fine Tuning call format has changed. You will now need to use this with gpt 3.5:

from openai import OpenAI
client = OpenAI()

client.fine_tuning.jobs.create(
training_file="you_training_file",
model="gpt-3.5-turbo"
)
Creating Email Data in Chat GPT4:43
Fine Tuning call format has changed. You will now need to use this with gpt 3.5:

from openai import OpenAI
client = OpenAI()

client.fine_tuning.jobs.create(
training_file="you_training_file",
model="gpt-3.5-turbo"
)
Data Preparation and Fine-Tune2:59
Fine Tuning call format has changed. You will now need to use this with gpt 3.5:

from openai import OpenAI
client = OpenAI()

client.fine_tuning.jobs.create(
training_file="you_training_file",
model="gpt-3.5-turbo"
)
Using the Email Organizer3:43
Fine Tuning call format has changed. You will now need to use this with gpt 3.5:

from openai import OpenAI
client = OpenAI()

client.fine_tuning.jobs.create(
training_file="you_training_file",
model="gpt-3.5-turbo"
)

Generating Company Review Tweets in Chat GPT1:44
It looks like OpenAI changed their chat completion calls.
You will now need to make sure the class OpenAI is imported like this:

from openai import OpenAI

and you will need to create an object based on the OpenAI Class like this:

client = OpenAI()
client.completions.create(model='gpt-3.5-turbo-instruct')

You will also need to change you model to this: model="gpt-3.5-turbo-instruct", as gpt 3 is deprecated.
Preparing Our Data and Running Fine-Tune1:57
It looks like OpenAI changed their chat completion calls.
You will now need to make sure the class OpenAI is imported like this:

from openai import OpenAI

and you will need to create an object based on the OpenAI Class like this:

client = OpenAI()
client.completions.create(model='gpt-3.5-turbo-instruct')

You will also need to change you model to this: model="gpt-3.5-turbo-instruct", as gpt 3 is deprecated.
Using Fine-Tuned Model2:29
It looks like OpenAI changed their chat completion calls.
You will now need to make sure the class OpenAI is imported like this:

from openai import OpenAI

and you will need to create an object based on the OpenAI Class like this:

client = OpenAI()
client.completions.create(model='gpt-3.5-turbo-instruct')

You will also need to change you model to this: model="gpt-3.5-turbo-instruct", as gpt 3 is deprecated.

Image Generation5:06
Please check the Open AI's documentation for any updates to their API calls here:

https://platform.openai.com/docs/api-reference/introduction

The image generation call format has changed:

from openai import OpenAI
client = OpenAI()

client.images.generate(
model="dall-e-3",
prompt="A cute baby sea otter",
n=1,
size="1024x1024"
)
Image Editing4:13
Please check the Open AI's documentation for any updates to their API calls here:

https://platform.openai.com/docs/api-reference/introduction

The image generation call format has changed:

from openai import OpenAI
client = OpenAI()

client.images.generate(
model="dall-e-3",
prompt="A cute baby sea otter",
n=1,
size="1024x1024"
)
Image Variation1:51
The image variation call format has changed:
from openai import OpenAI
client = OpenAI()

response = client.images.create_variation(
image=open("image_edit_original.png", "rb"),
n=2,
size="1024x1024"
)

Whisper Intro0:19
The calls for Whisper text generation have changed. Please use this with your file names:

from openai import OpenAI
client = OpenAI()

audio_file = open("speech.mp3", "rb")
transcript = client.audio.transcriptions.create(
model="whisper-1",
file=audio_file
)
Transcription2:03
The calls for Whisper text generation have changed. Please use this with your file names:

from openai import OpenAI
client = OpenAI()

audio_file = open("speech.mp3", "rb")
transcript = client.audio.transcriptions.create(
model="whisper-1",
file=audio_file
)
PyAudio and Wave Modules for Voice Recording5:14
Translation1:26
Please use this for translation generation as their API calls have changed:
from openai import OpenAI
client = OpenAI()

audio_file = open("speech.mp3", "rb")
transcript = client.audio.translations.create(
model="whisper-1",
file=audio_file
)

App Overview1:36
CustomTkinter Python UI Demo9:02
Feel free to skip the UI Tutorials and grab the code resources in the next 3 videos if you want to focus on the API only!
Initializing Window5:54
Creating Text Column UI10:05
Create a text column UI in custom Kinter with a label, prompt box, generation button, and a text completion area, arranged by grid with padding and appearance mode toggle.
Creating Image Column UI12:52
Design and configure an image column UI with light and dark color schemes, an image generation label, a 1–5 image number dropdown, and a central image button.
Creating Audio Column UI11:48
Design and implement an audio transcription column in a Tkinter UI, including a voice-to-text label, recording button, transcription and translation toggles, a transcript text box, and a scrollable recordings frame.

Generating Text Functionality4:51
Add dark and light modes and wire an appearance mode switch. Enable text generation by loading the API key, calling OpenAI chat with GPT-3.5 Turbo, and displaying the result.
Converting URL to Image4:33
Generating Image Functionality10:28
learn how to add dynamic image generation in a python app using openai's image api, including dropdown-driven image counts, segmented buttons, and downloadable image urls.
Image Variation Functionality and Download7:07
Transcription and Translation Functionality13:26
Implement voice-to-text with a recording button that toggles color and runs a background thread to record audio, save as wave files, and display transcription or translation using OpenAI whisper.
Adding Recall and Playback Buttons10:43
Add recall switches and play buttons to a scrollable voice-to-text frame with per-file identifiers for independent control. Wire transcription and playback for each recording using playsound version 1.20.2.
Congratulations on Completing the Course!0:14
Master confidence in using OpenAI's API to develop your own apps and drive future innovation with ChatGPT, image generation, and speech-to-text capabilities.

Requirements

Beginner level in python and a desire to learn.

Description

Are you ready to unlock the full potential of OpenAI's Python API? Join our comprehensive online course where you'll embark on a transformative journey, mastering the art of harnessing OpenAI's cutting-edge technologies to revolutionize your projects and propel your startups to new heights of efficiency and success.

In this course, you'll delve into the world of OpenAI's GPT models. You'll discover how to generate captivating and coherent text that captures the imagination of your audience. From crafting engaging stories to automating content creation, you'll learn the secrets to leveraging the immense power of language generation. You'll gain hands-on experience in generating, editing, and creating captivating variations of images with the DallE model, pushing the boundaries of creativity and visual expression. You'll master the art of extracting insights from audio data with the Whisper model, whether it's transcribing interviews, creating multilingual transcripts, or enabling voice-controlled applications.

The course goes beyond mere exploration. You'll discover how to fine-tune chat models to conduct sentiment analysis, intelligently organize your emails, and act as customer service chatbots. With sentiment analysis, you'll uncover the hidden emotions within textual data, gaining invaluable insights for business-oriented decision-making.

In the final project of this course, you'll embark on a thrilling endeavor to create a modern, user-friendly application that combines text and image generation, voice transcription and translation, all within a single app interface. What's more, you'll have the opportunity to integrate your fine-tuned models, giving your application a unique edge in the market.

Don't miss this chance to master OpenAI's Python API. Enroll now and revolutionize your startup with the limitless possibilities of AI. Together, let's unleash the power of OpenAI and embark on a journey of innovation and success!

Who this course is for:

Python developers aiming to explore the extensive possibilities in the latest OpenAI Python API

OpenAI Python API Startup: ChatGPT, Image Gen, Speech-Text+

What you'll learn

Explore related topics

Course content

Welcome to the Course!9 lectures • 14min

Text Generation and Chatbot6 lectures • 17min

Email Organizer Fine-Tuned Model4 lectures • 12min

Sentiment Analysis Fine-Tuned Model3 lectures • 6min

DallE Image Generation, Editing, and Variation3 lectures • 11min

Whisper Transcription and Translation4 lectures • 9min

Final AI App Project6 lectures • 51min

Adding AI Functionality to our App7 lectures • 51min

Requirements

Description

Who this course is for: