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How to Build a Custom AI Assistant in 30 Minutes: A Step-by-Step Tutorial

1. Setting Up Your Python Environment

• Install Python 3.9+ and create a virtual environment using python -m venv venv.
• Install required libraries: pip install openai python-dotenv flask.
• Set up a .env file to securely store your API key (never commit it to Git).

2. Getting Your OpenAI API Key

• Sign up at platform.openai.com and navigate to the API keys section.
• Create a new secret key, copy it immediately, and paste it into your .env file as OPENAI_API_KEY=your_key.
• Set a usage limit in your OpenAI dashboard to avoid unexpected charges during testing.

3. Writing the Core Chat Loop

• Use the openai.ChatCompletion.create() method with the gpt-3.5-turbo model for cost‑effective responses.
• Structure the conversation as a list of message objects (role: system, user, assistant).
• Implement a simple while True loop that takes user input, sends it to the API, and prints the assistant’s reply.

4. Adding Context and Memory

• Maintain a messages list that grows with each exchange to preserve conversation history.
• Truncate older messages when the token count approaches the model’s limit (e.g., 4096 tokens).
• Optionally store conversation history in a JSON file so the assistant “remembers” across sessions.

5. Deploying as a Simple Web App

• Use Flask to create a single‑page app with a form for user input and a div for the chat log.
• Create a /chat
  

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