Working with Deepseek in Pixeltable
Pixeltable's Deepseek integration enables you to access Deepseek's LLM via the Deepseek API.
This notebook demonstrates how to use Black Forest Labs (BFL) FLUX models for image generation and editing through Pixeltable.
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 pixeltable
BFL_API_KEYbfl.generate()bfl.edit()bfl.expand()bfl.fill()pxt.create_table()add_computed_column()insert()# Create a table for image generationprompts_t = pxt.create_table('bfl_demo.prompts',{'prompt': pxt.String, 'style': pxt.String},if_exists='replace',)# Add a computed column that generates images from promptsprompts_t.add_computed_column(image=bfl.generate(prompts_t.prompt, model='flux-pro-1.1', width=1024, height=1024))
One cell of the notebook, copied as it is. Open it in Colab for the rest.
Pixeltable's Deepseek integration enables you to access Deepseek's LLM via the Deepseek API.
Pixeltable's fal.ai integration enables you to access fal.ai's fast inference models via the fal.ai API.
Pixeltable's Microsoft Fabric integration enables you to access Azure OpenAI models within Microsoft Fabric notebook environments with automatic authentication.
Pixeltable's Fireworks integration enables you to access LLMs hosted on the Fireworks platform.