Complete Chatbot Development using ChatGPT API - 2025

Master basic Python fundamentals for building chatbots with the ChatGPT API, using beginner-friendly examples with Streamlit and essential programming concepts.

Install python, verify the version in the terminal, and fix path issues by updating the system environment variable; then install Sublime Text and run a hello world program to practice.

Explore strings with quotes, integers and floating point numbers, and booleans, then learn variables and basic printing in Python, using f-strings and formatting for dynamic output.

Explore Python data types: lists, sets, tuples, range, and dictionaries, and understand mutability, uniqueness, and key-value pairs. Apply operations like indexing, len, insertion, deletion, and using for loops.

Learn how to use conditions to control program flow with if, elif, and else statements in Python, and document code with comments for clarity.

Explore loops, including for and while, and master writing reusable functions with def; organize code with modules, importing user defined and built in options for scalable projects.

Explore object oriented programming in python by defining classes as blueprints and creating objects as class instances, with methods using self and initializing attributes via __init__.

Explore OpenAI and ChatGPT, and learn about OpenAI models, tokens, and temperatures, along with API usage policies, as we prepare to work with the systems API.

Explore how OpenAI enables ChatGPT API integration for web and mobile apps, and compare GPT-3.5 and GPT-4, including token pricing for input and output and prompt guidance.

Explore tokens as the currency of OpenAI GPT models, with input-output examples and a price breakdown, and learn how temperature from 0 to 2 shapes response in the playground.

Learn to navigate the OpenAI usage policy, ensuring safe, responsible use of OpenAI models and tools, with rules on illegal activities, malware, adult content, and account consequences.

Prepare chatbot development by reviewing essential tools, using Google Colab, and setting up GitHub and Streamlit Community Cloud to publish with an Ngrok token and GPT API.

Learn to set up tools for chatbot development with the ChatGPT API. Use Google Colab or your preferred editor, Streamlit for the web app, and Ngrok for public hosting.

Learn to use Google Colab for chatbot development: create and run notebooks, explore variables, use scratch cells, access code samples, and explore GitHub and Streamlit.

Learn Git and GitHub basics—repositories, branches, and version control—to track code changes, then publish Python projects publicly via Streamlit Community Cloud.

Learn how Ngrok exposes a local web app to the internet, view chatbot results, and set up authentication tokens, plus obtaining an OpenAI API key for the ChatGPT API.

Create your first chatbot using Streamlit and Ngrok, integrate the ChatGPT API key, and build a simple TripAdvisor chatbot.

Learn to build and run a Streamlit app in Google Colab, install Streamlit and Pinegrove, create app.py, and expose it publicly with Ngrok.

Learn to enhance a Streamlit app by using subheader, info, slider, button, text input, checkbox, sidebar, and select box with pandas dataframes for interactive features.

Learn to use the ChatGPT API to generate responses by installing OpenAI, configuring your API key, and calling chat.completion.create with GPT-3.5 turbo and system and user messages.

Develop an advanced Trip Advisor chatbot using Streamlit and OpenAI GPT-3.5 turbo to enable efficient AI conversations with system and user messages, including ngrok tunneling and a public UI.

Finalize your chat bot, create a GitHub repository, and deploy publicly with Streamlit Community Cloud, replacing ngrok hosting, then assess performance through interactive questions.

Prepare the TripAdvisor chatbot code for Streamlit community cloud by removing Ngrok, integrating Streamlit secrets for the API key, and creating app.py and requirements.txt for GitHub sharing.

Upload the project file to a public GitHub repository named chatbot with a readme and MIT license, then commit and upload to make it accessible on the Streamlit cloud.

Deploy your chatbot to Streamlit Community Cloud via GitHub, setting the main file path to app.py. Manage deployment, add OpenAI API key in secrets, and share the live link.

Evaluate the chatbot's performance by testing responses, flow, and emoji usage to ensure it functions as expected. Confirm its TripAdvisor persona and handling of reversed prompts during a live interaction.

Experiment with prompt manipulation to tailor a TripAdvisor chatbot, and publish apps using Ngrok for hosting and Streamlit Community Cloud via GitHub, followed by evaluating all chatbots' performance.

Create the final TripAdvisor chatbot by organizing a prompt and uploading an image, then run Ngrok-enabled code to test travel advisor responses.

Integrate two chatbots in one app by using phase one for the TripAdvisor chatbot and phase two for the business advisor chatbot, with a streamlit multipage interface.

Shows how to extend the app with PS3, PS4, and PS5, adding diverse prompts for trip advisor, business adviser, dream interpreter, prompt teacher, and security specialist.

Perform a systematic performance analysis of multiple chatbots, verifying proper functioning, adherence to prompts, and accurate responses across TripAdvisor, business advisor, dream interpreter, prompt teacher, and security specialist prompts.