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Build Your First AI-Powered Chatbot: A Step-by-Step Tutorial
1. Setting Up Your Development Environment
- Install Python 3.9+ and create a virtual environment to isolate dependencies.
- Use pip to install required libraries:
openai,python-dotenv, and optionallyflaskfor the web interface. - Set up a
.envfile to securely store your API key and other configuration variables.
2. Getting Your OpenAI API Key
- Sign up or log in to the OpenAI platform and navigate to the API keys section.
- Create a new secret key and copy it immediately – you won’t be able to see it again.
- Add the key to your
.envfile asOPENAI_API_KEY=your_key_here.
3. Writing the Core Chatbot Logic
- Import the
openailibrary and load your API key from the environment. - Define a function that sends a user message to the Chat Completion endpoint (e.g.,
gpt-3.5-turbo) and returns the assistant’s reply. - Implement a simple command-line loop that takes user input, calls the function, and prints the response.
4. Adding Memory and Context
- Maintain a conversation history list that stores both user and assistant messages as dictionaries.
- Pass the entire history to the
messagesparameter so the model remembers previous turns. - Limit the history length (e.g., last 10 exchanges) to stay within token limits and reduce costs.
5. Creating a Simple Web Interface (Optional)
- Use Flask to create a single-page app
AI Automation Playbook
Step-by-step workflows for automating content, email, social media, and research with AI agents.


