Build a ChatGPT Deep Research Clone with Streamlit
Course description
Imagine having your own AI assistant that conducts deep research for you: figuring out exactly what you need, searching for information online, collecting data, and presenting it in the form of a neat report or essay...
This is exactly what the Deep Research tool from ChatGPT does!
It is a powerful tool that allows you to use AI to explore complex topics and generate substantiated reports with sources.
And what could be better?
Create your own version of Deep Research!
In this course, you will step by step build your own clone of Deep Research. You will program all the stages - from query recognition and data collection to report writing - using Python and modern GPT models. This will not only give you the ability to adapt the tool to your needs but also help you understand how AI works on the inside.
Most importantly, you will package it all into a convenient web application on Streamlit and deploy it.
No "filler" - just practical code, clear explanations, and a result that you can actually use.
By the end of the course, you will have your own AI tool for deep research and the skills to create others.
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All Course Lessons (18)
| # | Lesson Title | Duration | Access |
|---|---|---|---|
| 1 | Introduction Demo | 09:04 | |
| 2 | Colab Setup | 02:35 | |
| 3 | Inputs | 02:19 | |
| 4 | 5 Clarifying Questions | 05:29 | |
| 5 | Answering the 5 Questions | 05:07 | |
| 6 | Define Goals and Queries for the Research | 07:18 | |
| 7 | Web Search with OpenAI | 05:10 | |
| 8 | Define Web Search Function | 02:09 | |
| 9 | Confirm if Goal Was Achieved | 06:21 | |
| 10 | Web Search if the Goal Was Not Achieved | 05:52 | |
| 11 | Final Deep Research Report | 04:38 | |
| 12 | Download Cursor | 04:37 | |
| 13 | .env File | 01:48 | |
| 14 | Prompt Cursor to Build the Streamlit App | 07:24 | |
| 15 | Launching the App Locally | 06:33 | |
| 16 | Debugging | 07:58 | |
| 17 | Push to Github | 09:07 | |
| 18 | Deploy to Streamlit | 05:58 |
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