Name: How to control your 🚁 drone using #Azure OpenAI or OpenAI APIs and Semantic Kernel
Rating: 4.9 (2976 reviews)
Author: elbruno

Coding4Fun Drone 🚁 posts

Hi!

In my previous post, I wrote about how we can use ChatGPT to generate Python code to control a drone.

Today, we are going to use Azure OpenAI Services or OpenAI APIs to generate the same code using GPT models.

We are going to use the same prompt that we had for ChatGPT.


Use this python code as reference 

[CODE START]
# display battery level
sendReadCommand('battery?')
print(f'Battery: {battery} %')

# take off
sendCommand("takeoff") 

# flip the drone left
sendCommand("flip l") 

# move drone up 5 cms
sendCommand("up 5") 

# move drone left 5 cms
sendCommand("left 5") 

# rotate drone clock wise 90 degrees
sendCommand("cw 90") 

# land the drone
sendCommand("land") 

[CODE END]

Generate code to takeoff the drone, flip right, move down 30 centimeters and land

Running this prompt in Azure OpenAI Studio generates the correct Python code:

Both Azure OpenAI Services and OpenAI APIs have amazing SDKs, however, I’ll use semantic kernel to have a single code base that can use both.

_ Note: This is the best way to learn semantic kernel for NET and Python:_

Start learning how to use Semantic Kernel.

Now, let’s create a simple function that:

Use semantic kernel to generate drone commands
Use Azure OpenAI Services or OpenAI APIs to generate drone commands
Use the semantic skill “DroneAI” to generate drone commands
Return the generated drone commands as a string

Here is the function code:

And, I need to have a Skill directory with my DroneAI skill. Something like this:

Here is the config.json content:


{
  "schema": 1,
  "description": "Generate commands to control the drone",
  "type": "completion",
  "completion": {
    "max_tokens": 1000,
    "temperature": 0.0,
    "top_p": 1.0,
    "presence_penalty": 0.0,
    "frequency_penalty": 0.0
  },
  "input": {
    "parameters": [
      {
        "name": "input",
        "description": "commands for the drone",
        "defaultValue": ""
      }
    ]
  }
}

And the skprompt.txt:


Use this python code as reference 

[CODE START]
# display battery level
sendReadCommand('battery?')
print(f'Battery: {battery} %')

# take off
sendCommand("takeoff") 

# flip the drone left
sendCommand("flip l") 

# move drone up 5 cms
sendCommand("up 5") 

# move drone left 5 cms
sendCommand("left 5") 

# rotate drone clock wise 90 degrees
sendCommand("cw 90") 

# land the drone
sendCommand("land")
[CODE END]

Generate python code only to follow these orders
{{$input}}
+++++

And that’s it! We can test this function with 2 unit tests for for platforms:


import unittest
from DroneGenCommandsWithAI import generate_drone_commands

class TestGenerateDroneCommands(unittest.TestCase):

    test_command = "takeoff the drone, flip right, move down 30 centimeters and land the drone"

    def test_generate_drone_commandsusing_openAI(self):
        print('###############################################')
        print(' Test using OpenAI APIs')
        commands = generate_drone_commands(self.test_command)

        # validate if the generated string contains the drone commands
        self.assertIn('takeoff', commands)
        self.assertIn('flip r', commands)
        self.assertIn('down 30', commands)
        self.assertIn('land', commands)
        print('###############################################')

    def test_generate_drone_commandsusing_azureOpenAI(self):
        print('###############################################')
        print(' Test using AZURE OpenAI Services')
        commands = generate_drone_commands(self.test_command, True)

        # validate if the generated string contains the drone commands
        self.assertIn('takeoff', commands)
        self.assertIn('flip r', commands)
        self.assertIn('down 30', commands)
        self.assertIn('land', commands)

if __name__ == ' __main__':
    unittest.main()

And, they both works!

In the next post we will review some options and configurations necessary for the correct code generation.

Happy coding!

Greetings

El Bruno