Working with OpenAI in Pixeltable
Pixeltable's OpenAI integration enables you to access OpenAI models via the OpenAI API.
Ollama is a popular platform for local serving of LLMs. In this tutorial, we'll show how to integrate Ollama models into a Pixeltable workflow.
Providers · Notebook · Updated
Colab runs it in your browser. If it calls a model provider, it asks for that provider's API key in a cell.
pip install ollama pixeltable
ollama.chat()pxt.create_table()add_computed_column()insert()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 responsest.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},))
One cell of the notebook, copied as it is. Open it in Colab for the rest.
Pixeltable's OpenAI integration enables you to access OpenAI models via the OpenAI API.
Pixeltable's OpenRouter integration enables you to access multiple LLM providers through a unified API via OpenRouter.
Pixeltable's Pydantic integration enables type-safe data insertion using Pydantic models. Instead of inserting raw dictionaries, you can define structured models with validation and insert them directly into Pixeltable tables.
Pixeltable's Replicate integration enables you to access Replicate's models via the Replicate API.