Explore Workers AI Models Using a Jupyter Notebook

A handy way to explore all of the models available on Workers AI is to use a Jupyter Notebook Open external link .

You can download the Workers AI notebook or view the embedded notebook below.

​​ Explore the Workers AI API using Python

Workers AI allows you to run machine learning models, on the Cloudflare network, from your own code – whether that be from Workers, Pages, or anywhere via REST API.

This notebook will explore the Workers AI REST API using Python and the requests Open external link library.

import sys
!{sys.executable} -m pip install requests python-dotenv

Requirement already satisfied: requests in ./venv/lib/python3.12/site-packages (2.31.0)
Requirement already satisfied: python-dotenv in ./venv/lib/python3.12/site-packages (1.0.1)
Requirement already satisfied: charset-normalizer<4,>=2 in ./venv/lib/python3.12/site-packages (from requests) (3.3.2)
Requirement already satisfied: idna<4,>=2.5 in ./venv/lib/python3.12/site-packages (from requests) (3.6)
Requirement already satisfied: urllib3<3,>=1.21.1 in ./venv/lib/python3.12/site-packages (from requests) (2.1.0)
Requirement already satisfied: certifi>=2017.4.17 in ./venv/lib/python3.12/site-packages (from requests) (2023.11.17)

import os

from IPython.display import display, Image, Markdown, Audio
from getpass import getpass

import requests

%load_ext dotenv
%dotenv

​​ Configuring your environment

To use the API you’ll need your Cloudflare Account ID Open external link (head to Workers & Pages > Overview > Account details > Account ID) and a Workers AI enabled API Token Open external link .

If you want to add these files to your environment, you can create a new file named .env

CLOUDFLARE_API_TOKEN="YOUR-TOKEN"
CLOUDFLARE_ACCOUNT_ID="YOUR-ACCOUNT-ID"

if "CLOUDFLARE_API_TOKEN" in os.environ:
    api_token = os.environ["CLOUDFLARE_API_TOKEN"]
else:
    api_token = getpass("Enter you Cloudflare API Token")

if "CLOUDFLARE_ACCOUNT_ID" in os.environ:
    account_id = os.environ["CLOUDFLARE_ACCOUNT_ID"]
else:
    account_id = getpass("Enter your account id")

​​ Explore tasks available on the Workers AI Platform

​​ Text Generation

Explore all Text Generation Models

model = "@cf/meta/llama-3-8b-instruct"

response = requests.post(
    f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/{model}",
    headers={"Authorization": f"Bearer {api_token}"},
    json={"messages": [
        {"role": "system", "content": "You are a productivity assistant for users of Jupyter notebooks for both Mac and Windows users. Respond in Markdown."},
        {"role": "user", "content": "How do I use keyboard shortcuts to execute cells?"}
    ]}
)

inference = response.json()
display(Markdown(inference["result"]["response"]))

Great question! 😊

​​ Mac Users:

To execute cells using keyboard shortcuts on a Mac, you can use the following combinations:

​​ Windows Users:

On Windows, you can use the following keyboard shortcuts to execute cells:

Tips:

• You can also use the F5 key to execute the current cell on both Mac and Windows.

​​ Text to Image

Explore all Text to Image models

model = "@cf/stabilityai/stable-diffusion-xl-base-1.0"

response = requests.post(
    f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/{model}",
    headers={"Authorization": f"Bearer {api_token}"},
    json={"prompt": "A pencil drawing of an excited developer using an API"}
)

display(Image(response.content))

​​ Translations

Explore all Translation models

model = "@cf/meta/m2m100-1.2b"

response = requests.post(
    f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/{model}",
    headers={"Authorization": f"Bearer {api_token}"},
    json={
        "text": "Artificial intelligence is pretty impressive these days. What do you think?",
        "source_lang": "english",
        "target_lang": "spanish"
    }
)

inference = response.json()
print(inference["result"]["translated_text"])

La inteligencia artificial es bastante impresionante en estos días. ¿Qué piensas?

​​ Text Classification

Explore all Text Classification models

model = "@cf/huggingface/distilbert-sst-2-int8"

response = requests.post(
    f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/{model}",
    headers={"Authorization": f"Bearer {api_token}"},
    json={"text": "This taco is delicious"}
)

inference = response.json()
inference["result"]

[{'label': 'NEGATIVE', 'score': 0.00012679687642958015},
 {'label': 'POSITIVE', 'score': 0.999873161315918}]

​​ Automatic Speech Recognition

Explore all Speech Recognition models

model = "@cf/openai/whisper"

url = "https://raw.githubusercontent.com/craigsdennis/notebooks-cloudflare-workers-ai/main/assets/craig-rambling.mp3"
display(Audio(url))
audio = requests.get(url)

response = requests.post(
    f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/{model}",
    headers={"Authorization": f"Bearer {api_token}"},
    data=audio.content
)

inference = response.json()
inference

{'result': {'text': "Hello there, I'm making a recording for a Jupiter notebook. That's a Python notebook, Jupiter, J-U-P-Y-T-E-R. Not to be confused with the planet. Anyways, let me hear you. I'm gonna talk a little bit. I'm gonna make a little bit of noise. Say some hard words. I'm gonna say Kubernetes. I'm not actually even talking about Kubernetes. I just want to see if they can do Kubernetes. Anyway, this is a test of transcription and let's see how we're dead!",
  'word_count': 86,
  'words': [{'word': 'Hello',
    'start': 0.30000001192092896,
    'end': 0.7599999904632568},
   {'word': 'there,', 'start': 0.7599999904632568, 'end': 1.2799999713897705},
   {'word': "I'm", 'start': 1.2799999713897705, 'end': 1.5},
   {'word': 'making', 'start': 1.5, 'end': 1.7000000476837158},
   {'word': 'a', 'start': 1.7000000476837158, 'end': 1.8600000143051147},
   {'word': 'recording',
    'start': 1.8600000143051147,
    'end': 2.2799999713897705},
   {'word': 'for', 'start': 2.2799999713897705, 'end': 2.680000066757202},
   {'word': 'a', 'start': 2.680000066757202, 'end': 2.799999952316284},
   {'word': 'Jupiter', 'start': 2.799999952316284, 'end': 3.259999990463257},
   {'word': 'notebook.',
    'start': 3.259999990463257,
    'end': 3.6600000858306885},
   {'word': "That's", 'start': 3.6600000858306885, 'end': 4.300000190734863},
   {'word': 'a', 'start': 4.300000190734863, 'end': 4.380000114440918},
   {'word': 'Python', 'start': 4.380000114440918, 'end': 4.699999809265137},
   {'word': 'notebook,', 'start': 4.699999809265137, 'end': 5.480000019073486},
   {'word': 'Jupiter,', 'start': 5.480000019073486, 'end': 6.440000057220459},
   {'word': 'J', 'start': 6.440000057220459, 'end': 6.619999885559082},
   {'word': '-U', 'start': 6.619999885559082, 'end': 6.960000038146973},
   {'word': '-P', 'start': 6.960000038146973, 'end': 7.179999828338623},
   {'word': '-Y', 'start': 7.179999828338623, 'end': 7.460000038146973},
   {'word': '-T', 'start': 7.460000038146973, 'end': 7.739999771118164},
   {'word': '-E', 'start': 7.739999771118164, 'end': 7.940000057220459},
   {'word': '-R.', 'start': 7.940000057220459, 'end': 8.34000015258789},
   {'word': 'Not', 'start': 8.520000457763672, 'end': 8.899999618530273},
   {'word': 'to', 'start': 8.899999618530273, 'end': 9.34000015258789},
   {'word': 'be', 'start': 9.34000015258789, 'end': 9.4399995803833},
   {'word': 'confused', 'start': 9.4399995803833, 'end': 9.760000228881836},
   {'word': 'with', 'start': 9.760000228881836, 'end': 9.979999542236328},
   {'word': 'the', 'start': 9.979999542236328, 'end': 10.0600004196167},
   {'word': 'planet.', 'start': 10.0600004196167, 'end': 10.699999809265137},
   {'word': 'Anyways,', 'start': 10.699999809265137, 'end': 12.15999984741211},
   {'word': 'let', 'start': 12.15999984741211, 'end': 12.4399995803833},
   {'word': 'me', 'start': 12.4399995803833, 'end': 12.539999961853027},
   {'word': 'hear', 'start': 12.539999961853027, 'end': 12.720000267028809},
   {'word': 'you.', 'start': 12.720000267028809, 'end': 12.819999694824219},
   {'word': "I'm", 'start': 12.819999694824219, 'end': 12.899999618530273},
   {'word': 'gonna', 'start': 12.899999618530273, 'end': 12.960000038146973},
   {'word': 'talk', 'start': 12.960000038146973, 'end': 13.140000343322754},
   {'word': 'a', 'start': 13.140000343322754, 'end': 13.279999732971191},
   {'word': 'little', 'start': 13.279999732971191, 'end': 13.399999618530273},
   {'word': 'bit.', 'start': 13.399999618530273, 'end': 13.579999923706055},
   {'word': "I'm", 'start': 13.579999923706055, 'end': 13.680000305175781},
   {'word': 'gonna', 'start': 13.680000305175781, 'end': 13.739999771118164},
   {'word': 'make', 'start': 13.739999771118164, 'end': 13.9399995803833},
   {'word': 'a', 'start': 13.9399995803833, 'end': 14.220000267028809},
   {'word': 'little', 'start': 14.220000267028809, 'end': 14.4399995803833},
   {'word': 'bit', 'start': 14.4399995803833, 'end': 14.619999885559082},
   {'word': 'of', 'start': 14.619999885559082, 'end': 14.720000267028809},
   {'word': 'noise.', 'start': 14.720000267028809, 'end': 15.479999542236328},
   {'word': 'Say', 'start': 15.479999542236328, 'end': 15.880000114440918},
   {'word': 'some', 'start': 15.880000114440918, 'end': 16.020000457763672},
   {'word': 'hard', 'start': 16.020000457763672, 'end': 16.200000762939453},
   {'word': 'words.', 'start': 16.200000762939453, 'end': 16.520000457763672},
   {'word': "I'm", 'start': 16.520000457763672, 'end': 16.65999984741211},
   {'word': 'gonna', 'start': 16.65999984741211, 'end': 16.739999771118164},
   {'word': 'say', 'start': 16.739999771118164, 'end': 16.920000076293945},
   {'word': 'Kubernetes.',
    'start': 16.920000076293945,
    'end': 17.540000915527344},
   {'word': "I'm", 'start': 17.540000915527344, 'end': 17.68000030517578},
   {'word': 'not', 'start': 17.68000030517578, 'end': 17.739999771118164},
   {'word': 'actually',
    'start': 17.739999771118164,
    'end': 18.020000457763672},
   {'word': 'even', 'start': 18.020000457763672, 'end': 18.200000762939453},
   {'word': 'talking', 'start': 18.200000762939453, 'end': 18.420000076293945},
   {'word': 'about', 'start': 18.420000076293945, 'end': 18.639999389648438},
   {'word': 'Kubernetes.',
    'start': 18.639999389648438,
    'end': 18.940000534057617},
   {'word': 'I', 'start': 18.940000534057617, 'end': 19.260000228881836},
   {'word': 'just', 'start': 19.260000228881836, 'end': 19.3799991607666},
   {'word': 'want', 'start': 19.3799991607666, 'end': 19.520000457763672},
   {'word': 'to', 'start': 19.520000457763672, 'end': 19.600000381469727},
   {'word': 'see', 'start': 19.600000381469727, 'end': 19.739999771118164},
   {'word': 'if', 'start': 19.739999771118164, 'end': 19.899999618530273},
   {'word': 'they', 'start': 19.899999618530273, 'end': 19.979999542236328},
   {'word': 'can', 'start': 19.979999542236328, 'end': 20.100000381469727},
   {'word': 'do', 'start': 20.100000381469727, 'end': 20.31999969482422},
   {'word': 'Kubernetes.',
    'start': 20.31999969482422,
    'end': 21.399999618530273},
   {'word': 'Anyway,', 'start': 21.5, 'end': 21.799999237060547},
   {'word': 'this', 'start': 21.799999237060547, 'end': 21.940000534057617},
   {'word': 'is', 'start': 21.940000534057617, 'end': 22.040000915527344},
   {'word': 'a', 'start': 22.040000915527344, 'end': 22.15999984741211},
   {'word': 'test', 'start': 22.15999984741211, 'end': 22.31999969482422},
   {'word': 'of', 'start': 22.31999969482422, 'end': 22.639999389648438},
   {'word': 'transcription',
    'start': 22.639999389648438,
    'end': 23.15999984741211},
   {'word': 'and', 'start': 23.15999984741211, 'end': 23.639999389648438},
   {'word': "let's", 'start': 23.639999389648438, 'end': 24.100000381469727},
   {'word': 'see', 'start': 24.100000381469727, 'end': 24.31999969482422},
   {'word': 'how', 'start': 24.31999969482422, 'end': 24.579999923706055},
   {'word': "we're", 'start': 24.579999923706055, 'end': 24.81999969482422},
   {'word': 'dead!', 'start': 24.81999969482422, 'end': 26.139999389648438}]},
 'success': True,
 'errors': [],
 'messages': []}

​​ Image Classification

Explore all Image Classification models

model = "@cf/microsoft/resnet-50"

url = "https://raw.githubusercontent.com/craigsdennis/notebooks-cloudflare-workers-ai/main/assets/craig-and-a-burrito.jpg"
image_request = requests.get(url, allow_redirects=True)

display(Image(image_request.content, format="jpg"))
response = requests.post(
    f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/run/{model}",
    headers={"Authorization": f"Bearer {api_token}"},
    data=image_request.content
)

inference = response.json()
inference["result"]

[{'label': 'BURRITO', 'score': 0.9999678134918213},
 {'label': 'GUACAMOLE', 'score': 8.532096217095386e-06},
 {'label': 'BAGEL', 'score': 4.704045295511605e-06},
 {'label': 'SPATULA', 'score': 4.0899126361182425e-06},
 {'label': 'POTPIE', 'score': 3.0937740120862145e-06}]