ChatGPT & DeepSeek Apps : Creating AI Apps | AI Agents

Set up a Python development environment using Google Colab to build AI-powered apps with JetGPT and ChatGPT, installing the OpenAI library and configuring an API key to access GPT-4.

Explore OpenAI's documentation to master GPT-4, GPT-4 Mini, and GPT-4 Omni, and learn quickstart steps, prompt engineering, and retrieval augmented generation for API use.

Optimize ChatGPT for coding with seven tips, emphasizing clear prompts, breaking tasks into steps, code completion and refactoring, debugging, documentation, test cases, and exploring libraries and approaches.

Build and explain the Amazon AI voice assistant that uses speech recognition and text-to-speech, GPT-4, and Playwright to search Amazon, analyze products, and save data to CSV.

Learn to set up Chrome for testing in debug mode, using Playwright and Chromium.connect to a local Chrome instance for automated data scraping and testing, avoiding blocks.

Watch a live demo of running chrome in debug mode to search amazon for iPad 10 cases, perform product analysis, and export data with Playwright and GPT-4O mini.

Learn to build a Twitter scraper with Python and Playwright that collects live tweets into a CSV file by scrolling and avoiding duplicates, with an eye toward future LLM integration.

Test the essential part by automatically scrolling in Chromium to collect the latest tweets from a profile and save them to twits.csv.

Build a Twitter scraper powered by a large language model in Python, using Playwright, PyQt5, and OpenAI GPT-4o to extract tweets and chat with scraped data.

Run the twitter scraper llm to collect data from Elon Musk's profile, auto-scroll, and chat with the data about politics and technology, highlighting immigration and Tesla driverless features.

Introduce the open-source DeepSeek R1 reasoning model from China and compare it to ChatGPT. Show swapping OpenAI API calls with the DeepSeek API in a SaaS app.

Create and secure your first DeepSeek API key, explore the official API docs, set up a Google Colab notebook, and compare DeepSeek models for chat and reasoning.

Learn how to download and run a 1.5 billion parameter llm locally with Allama, compare api usage, privacy, and cost, and run it on a laptop.

Combine eleven labs voice generation with deep sig models to run AI chat locally, leveraging a llama model, text-to-speech, and streaming chat for responsive, on-device interactions.

Create a private, locally installed deep RL model to power an AI girlfriend and talking avatars, preserving conversation history and memory while avoiding data sharing with third-party API providers.

The lecture demonstrates building a local OCR and image understanding workflow using easy OCR or GPT-4 vision to extract text and describe images when the DeepSix API is down.

Run Db6 AR1 models locally and on google colab via hugging face, with a 1.5 billion-parameter chatbot; compare local hardware limits, colab constraints, and API-based deployment.

Discover how to build an AI real estate agent by integrating the Deep six API, using two functions to fetch listings and search results, with a reasoning step.

Migrate the Amazon jarvis app to the deep six r1 models api by swapping the api key and url, enabling Etsy search, scraping, and csv data export with db6 api.

Automate YouTube video creation by pulling Reddit data, selecting top and engaging posts, curating a one-minute video with subtitles and background visuals, and uploading daily with SEO.

Explore how Gemini with a search api retrieves data from search results without scraping, and see how it compares to ChatGPT’s interface using Google AI studio and Gemini 2.0 flash.

Demonstrate deploying a Chrome extension with GPT and the API, then use IFA to answer questions from the current webpage and add chat history to an LLM with LangChain.

Build a chrome extension that scrapes the current URL, uses ChatGPT to craft user interface elements, and connects to a public FastAPI API on Railway for data and report generation.

Complete the course to build ai powered apps with ChatGPT's API, troubleshoot and refactor, deploy with FastAPI, and explore three ai apps including Amazon AI voice assistant.