Working with Ollama in Pixeltable

# To install Ollama on colab, uncomment and run the following
# three lines (this will also work on a local Linux machine
# if you don't already have Ollama installed).

# !curl -fsSL https://ollama.com/install.sh | sh
# import subprocess
# ollama_process = subprocess.Popen(['ollama', 'serve'], stderr=subprocess.PIPE)

# To run the notebook against an instance of Ollama running on a
# remote server, uncomment the following line and specify the URL.

# os.environs['OLLAMA_HOST'] = 'https://127.0.0.1:11434'

%pip install -qU ollama

import ollama

ollama.pull('qwen3:0.6b')
ollama.generate('qwen3:0.6b', 'What is the capital of Missouri?')[
    'response'
]

%pip install -qU pixeltable

import pixeltable as pxt
from pixeltable.functions.ollama import chat

pxt.drop_dir('ollama_demo', force=True)
pxt.create_dir('ollama_demo')

t = pxt.create_table('ollama_demo/chat', {'input': pxt.String})

messages = [{'role': 'user', 'content': t.input}]

# Add a computed column that runs the model to generate responses
t.add_computed_column(
    output=chat(
        messages=messages,
        model='qwen3:0.6b',
        # These parameters are optional and can be used to tune model behavior:
        options={'max_tokens': 300, 'top_p': 0.9, 'temperature': 0.5},
    )
)

# Extract the message content into a separate column
t.add_computed_column(response=t.output.message.content)

# Start a conversation
t.insert(input='What are the most popular services for LLM inference?')
t.select(t.input, t.response).show()