Demo Migrating an Application to Use the OpenAI API

This guide shows you how to update a Flask-based AI app to use the OpenAI API in production while still developing locally with Ollama. By changing only a few environment variables, you can switch between free local development and cost-effective cloud inference.

1. Create an OpenAI API Key

The image shows a login page for OpenAI, offering options to sign in with an email address, phone, Google, Microsoft, or Apple accounts.

Navigate to Settings → API keys, then click Create new secret key.
Provide a name (e.g., “Ollama app”), assign it to your default project, set permissions, and copy the secret key.

The image shows a webpage for creating a new secret API key on the OpenAI platform, with a form to input details like name, project, and permissions.

Confirm that your new key appears under API keys.

The image shows a webpage from the OpenAI platform displaying API key management, with details of an API key named "ollama-app" including its secret key, creation date, and permissions.

::: note Keep your secret key safe. Do not commit it to version control. :::

2. Choose a Model

Open the Quickstart Guide or the Models Reference to compare models. In this demo, we’ll use gpt-4o-mini.

Environment	Endpoint	Model	Authentication
Local (Ollama)	http://localhost:11434	o1-mini	none
Production (OpenAI)	https://api.openai.com/v1	gpt-4o-mini	Bearer API Key

The image shows a webpage from the OpenAI API documentation, detailing flagship models like GPT-4o and their capabilities, along with a sidebar menu for navigation.

3. Update Your Environment Variables

In your project’s .env file, replace the Ollama endpoint with OpenAI’s and add your secret key:

OPENAI_API_KEY=your_openai_api_key_here
LLM_ENDPOINT="https://api.openai.com/v1"
MODEL=gpt-4o-mini

4. Update the Flask Server

Install the OpenAI Python client and python-dotenv if you haven’t already:

pip install openai python-dotenv Flask

import os
from flask import Flask, request, render_template_string
from openai import OpenAI
from dotenv import load_dotenv

load_dotenv()

app = Flask(__name__)

client = OpenAI(
    api_key=os.getenv("OPENAI_API_KEY"),
    base_url=os.getenv("LLM_ENDPOINT")
)

HTML_TEMPLATE = """
<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>AI-Generated Poem</title>
  <style>
    body { font-family: Arial, sans-serif; margin: 20px; background-color: #f8f9fa; }
    .container { max-width: 600px; margin: auto; }
  </style>
</head>
<body>
  <div class="container">
    <h1>AI Poem Generator</h1>
    <form method="post">
      <label for="prompt">Enter a prompt:</label><br>
      <input id="prompt" name="prompt" type="text" required style="width: 100%;"><br><br>
      <button type="submit">Generate Poem</button>
    </form>
    
      <h2>Generated Poem:</h2>
      <pre>{{ poem }}</pre>
    
  </div>
</body>
</html>
"""

@app.route("/", methods=["GET", "POST"])
def index():
    poem = None
    if request.method == "POST":
        prompt = request.form["prompt"]
        response = client.chat.completions.create(
            model=os.getenv("MODEL"),
            messages=[
                {"role": "system", "content": "You are a helpful assistant."},
                {"role": "user",   "content": prompt}
            ],
            store=True
        )
        poem = response.choices[0].message.content
    return render_template_string(HTML_TEMPLATE, poem=poem)

if __name__ == '__main__':
    app.run(port=3000)

::: warning Always use https://api.openai.com/v1. Requests over HTTP will be rejected with a 403 error. :::

5. Run and Test

Activate your virtual environment:
source ollama-app/bin/activate
Start the Flask server:
python server.py
In your browser, go to http://127.0.0.1:3000, enter a prompt (e.g., “a poem on birds”) and click Generate Poem.

If you accidentally point to http://api.openai.com, you’ll see:

Error code: 403 - {
  "error": {
    "code": "http_unsupported",
    "message": "The OpenAI API is only accessible over HTTPS. Ensure the URL starts with 'https://'."
  }
}

Switching to the https:// endpoint resolves this.

The image shows an AI Poem Generator interface with a text box for input and a button labeled "Generate Poem." Below, there's a section displaying an AI-generated poem.

With just an environment-variable tweak, your app seamlessly transitions from local Ollama LLMs to production-ready OpenAI models.

Getting Started With Ollama

Building AI Applications

Customising Models With Ollama

Introduction

Prerequisites

Demo Migrating an Application to Use the OpenAI API

1. Create an OpenAI API Key

2. Choose a Model

3. Update Your Environment Variables

4. Update the Flask Server

5. Run and Test

References

Watch Video

​1. Create an OpenAI API Key

​2. Choose a Model

​3. Update Your Environment Variables

​4. Update the Flask Server

​5. Run and Test

​References

Watch Video

1. Create an OpenAI API Key

2. Choose a Model

3. Update Your Environment Variables

4. Update the Flask Server

5. Run and Test

References