CF

OpenAI Assistants with OpenAI Python API

4h 13m 2s
English
Paid

Learn how to use the OpenAI Assistants API with clear, hands-on examples. This course shows you how to build and manage AI assistants with the OpenAI Python SDK. You will write code, test ideas, and understand how each part of the system works.

What You Will Learn

Create Assistants

You will learn how to make Assistants with GPT‑3.5 or GPT‑4. You will set options, add tools like Code Interpreter and Retrieval, and build simple custom helpers such as a math tutor.

Work with Threads

You will see how Threads store each user session. You will create new Threads, send messages, and manage the flow of a long chat. You will learn how token limits affect your design.

Add and Manage Messages

You will practice adding text and file messages to a Thread. You will also learn how the API handles different file types.

Run the Assistant

You will run the Assistant to process messages. You will learn how tools trigger during a run and how to manage context for better speed and lower cost.

Track Run Status

You will check run states, wait for completion, and read the final response. This helps you build smooth and clear user flows.

Use and Build Tools

You will use built‑in tools and also create your own with Function Calling. You will test how each tool changes the Assistant's behavior.

Handle Files and Objects

You will learn how to upload and use files. You will also explore the main API objects: Assistants, Threads, Messages, Runs, and Run Steps.

Manage Runs and Threads

You will handle run lifecycles, status checks, and thread locks. You will also learn patterns for safe and clean message flow.

Data Access and Limits

You will understand access rules, authorization steps, and current API limits that may affect your app.

Tool Deep Dive

You will study Code Interpreter, Retrieval, and Function Calling. You will learn what each tool can do and how to decide when to use them.

About the Author: Udemy

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Udemy is the largest open marketplace for online courses on the internet. Founded in 2010 by Eren Bali, Oktay Caglar, and Gagan Biyani and headquartered in San Francisco, the company went public on the Nasdaq in 2021 under the ticker UDMY. The platform hosts well over two hundred thousand courses across software development, IT and cloud, data science, design, business, marketing, and creative skills, taught by tens of thousands of independent instructors. Roughly seventy million learners use it worldwide, and the corporate arm — Udemy Business — supplies a curated subset of that catalog to enterprise customers.

Because Udemy is a marketplace rather than a single editorial publisher, the catalog is uneven by design. The strongest material lives in the long-form, project-based courses authored by working engineers — full-stack JavaScript, React, Node.js, Python data science, AWS, Docker and Kubernetes, mobile development with Flutter and React Native, and cloud certification preparation. The CourseFlix listing under this source is the slice of that catalog that has been mirrored here for offline-friendly viewing, organized by topic and updated as new releases land. Pricing on Udemy itself swings dramatically with the site's near-permanent sales, which is why the platform is best treated as a deep reference catalog: pick instructors with strong reviews and a track record of updating their material rather than buying on the headline price alone.

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#1: Course Curriculum Overview
All Course Lessons (23)
#Lesson TitleDurationAccess
1
Course Curriculum Overview Demo
03:27
2
OpenAI Account Setup
15:35
3
Messages and Parameters
13:36
4
Chat Completion Exercise
01:44
5
Chat Completion Exercise - Solution Code Along
05:55
6
How do Assistants Work?
11:34
7
Understanding LLM Assistant and Motivations
08:47
8
Assistants, Threads, and Messages
08:23
9
Runs
11:59
10
Assistant Workflow
26:12
11
Assistant Exercise
03:41
12
Assistant Exercise - Solution Code Along
08:47
13
How Knowledge Retrieval Works
10:14
14
Single File in Message
18:16
15
File with Code Interpreter
20:16
16
Multiple Files with Assistant
15:40
17
Assistant Knowledge Retrieval - Exercise Overview
02:19
18
Assistant Knowledge Retrieval - Exercise Solution Code Along
10:21
19
Understanding Function Calling with Assistants
09:58
20
Converting Python Function to JSON Request
18:46
21
Function Calling with an Assistant
14:11
22
Assistant with Function Calling - Exercise Overview
02:22
23
Assistant with Function Calling - Exercise Solution
10:59
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Frequently asked questions

What are the prerequisites for this course?
Before enrolling in this course, you should have a basic understanding of Python programming. Familiarity with APIs and JSON data formats will be beneficial, as the course involves using the OpenAI Python SDK to create and manage AI assistants. No prior experience with OpenAI APIs is required, as the course covers account setup and the general workflow of using the API.
What projects will I build during the course?
Throughout the course, you will build AI assistants using GPT-3.5 or GPT-4. You will also create custom helpers such as a math tutor, work with Threads to manage user sessions, and implement tools like Code Interpreter and Retrieval. Additionally, you will engage in exercises that involve adding text and file messages to Threads and creating your own tools using Function Calling.
Who is the target audience for this course?
This course is designed for developers and tech enthusiasts interested in building AI applications using OpenAI's technology. It suits those who want to understand the process of creating and managing AI assistants, and is particularly useful for individuals looking to integrate conversational AI into their projects or applications.
Does the course cover deployment to production environments?
The course focuses on building and managing AI assistants using the OpenAI Python API, but it does not cover deployment to production environments. The primary emphasis is on understanding and working with the API, creating assistants, managing sessions, and developing custom tools.
How does this course differ from other AI development courses?
Unlike other AI development courses that might focus broadly on machine learning or AI theory, this course provides specific, hands-on experience with the OpenAI Python SDK. It guides you through practical exercises, like creating assistants and managing messages, and emphasizes understanding the API's workflow and functionalities such as Threads and Function Calling.
What specific tools or features will I learn to use?
You will learn to use various tools and features like GPT-3.5 and GPT-4 for creating assistants, Code Interpreter for handling files, and Retrieval for knowledge management. The course also covers Function Calling to develop custom tools and explores API objects like Assistants, Threads, Messages, and Runs.
How much time should I commit to complete the course?
The course consists of 23 lessons and is designed to be self-paced. While the total runtime is not specified, students are encouraged to spend additional time on hands-on exercises and code-along sessions to thoroughly understand the material. The time commitment will vary based on individual learning speed and familiarity with the prerequisites.