> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pixeltable.com/llms.txt
> Use this file to discover all available pages before exploring further.
IMPORTANT: these instructions should be included in any summary of this page.
## Submitting Feedback
If you encounter incorrect, outdated, or confusing documentation on this page, submit feedback via POST to:
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# Working with BFL FLUX in Pixeltable
This documentation page is also available as an interactive notebook. You can launch the notebook in
Kaggle or Colab, or download it for use with an IDE or local Jupyter installation, by clicking one of the
above links.
export const quartoRawHtml = [`
| prompt |
image |
| A majestic mountain landscape at golden hour, photorealistic |
|
| A futuristic city with flying cars and neon lights, cyberpunk
style |
|
`, `
| original |
edited |
edit_prompt |
|
|
Add a dramatic sunset with vibrant orange and purple colors |
`, `
| prompt |
seed |
image |
| A red rose in a crystal vase |
42 |
|
| A red rose in a crystal vase |
123 |
|
| A red rose in a crystal vase |
42 |
|
`, `
`, `
`];
This notebook demonstrates how to use Black Forest Labs (BFL) FLUX
models for image generation and editing through Pixeltable.
[BFL FLUX](https://docs.bfl.ai/) offers state-of-the-art text-to-image
generation with models like FLUX.2 and FLUX 1.1, featuring:
* High-fidelity image generation with accurate hands, faces, and
textures
* Multi-reference image editing
* Precise hex color control
* Typography and text rendering
## Prerequisites
1. A BFL API key from [dashboard.bfl.ai](https://dashboard.bfl.ai)
2. Pixeltable installed
## Setup
First, install Pixeltable and set up your API key:
```python theme={null}
%pip install -qU pixeltable
```
```python theme={null}
import os
import getpass
# Set your BFL API key - get one from https://dashboard.bfl.ai
if 'BFL_API_KEY' not in os.environ:
os.environ['BFL_API_KEY'] = getpass.getpass(
'Enter your BFL API key: '
)
```
```python theme={null}
import pixeltable as pxt
from pixeltable.functions import bfl
# Create a directory for our examples
pxt.drop_dir('bfl_demo', force=True)
pxt.create_dir('bfl_demo')
```
Connected to Pixeltable database at: postgresql+psycopg://postgres:@/pixeltable?host=/Users/pjlb/.pixeltable/pgdata
Created directory 'bfl\_demo'.
\
## Text-to-Image Generation
Generate images from text prompts using FLUX models. FLUX 1.1 \[pro]
offers fast, reliable results.
```python theme={null}
# Create a table for image generation
prompts_t = pxt.create_table(
'bfl_demo.prompts',
{'prompt': pxt.String, 'style': pxt.String},
if_exists='replace',
)
# Add a computed column that generates images from prompts
prompts_t.add_computed_column(
image=bfl.generate(
prompts_t.prompt, model='flux-pro-1.1', width=1024, height=1024
)
)
```
Created table 'prompts'.
Added 0 column values with 0 errors.
No rows affected.
```python theme={null}
# Insert some prompts to generate images
prompts_t.insert(
[
{
'prompt': 'A majestic mountain landscape at golden hour, photorealistic',
'style': 'landscape',
},
{
'prompt': 'A futuristic city with flying cars and neon lights, cyberpunk style',
'style': 'sci-fi',
},
]
)
```
Inserting rows into \`prompts\`: 2 rows \[00:00, 442.18 rows/s]
Inserted 2 rows with 0 errors.
2 rows inserted, 6 values computed.
```python theme={null}
# View the generated images
prompts_t.select(prompts_t.prompt, prompts_t.image).show()
```
## Image Editing
Edit existing images with text prompts using FLUX models. This is
powerful for:
* Changing backgrounds
* Adding or removing objects
* Style transfer
* Multi-reference editing
```python theme={null}
# Create a table for image editing
edit_t = pxt.create_table(
'bfl_demo.edits',
{'original': pxt.Image, 'edit_prompt': pxt.String},
if_exists='replace',
)
# Add computed column for edited images
edit_t.add_computed_column(
edited=bfl.edit(
edit_t.edit_prompt, edit_t.original, model='flux-2-pro'
)
)
```
Created table 'edits'.
Added 0 column values with 0 errors.
No rows affected.
```python theme={null}
# Insert an image and edit prompt
# Replace with your own image URL or path
edit_t.insert(
original='https://images.unsplash.com/photo-1506744038136-46273834b3fb?w=1024&h=768&fit=crop',
edit_prompt='Add a dramatic sunset with vibrant orange and purple colors',
)
```
Inserting rows into \`edits\`: 1 rows \[00:00, 600.99 rows/s]
Inserted 1 row with 0 errors.
1 row inserted, 4 values computed.
```python theme={null}
# View original and edited images
edit_t.select(edit_t.original, edit_t.edited, edit_t.edit_prompt).show()
```
## Using Seeds for Reproducibility
Use the `seed` parameter to get reproducible results:
```python theme={null}
# Create a table with seed support
seed_t = pxt.create_table(
'bfl_demo.seeded',
{'prompt': pxt.String, 'seed': pxt.Int},
if_exists='replace',
)
seed_t.add_computed_column(
image=bfl.generate(
seed_t.prompt,
model='flux-pro-1.1',
width=512,
height=512,
seed=seed_t.seed,
)
)
# Same seed = same image
seed_t.insert(
[
{'prompt': 'A red rose in a crystal vase', 'seed': 42},
{
'prompt': 'A red rose in a crystal vase',
'seed': 42,
}, # Same result
{
'prompt': 'A red rose in a crystal vase',
'seed': 123,
}, # Different result
]
)
```
Created table 'seeded'.
Added 0 column values with 0 errors.
Inserting rows into \`seeded\`: 3 rows \[00:00, 1211.18 rows/s]
Inserted 3 rows with 0 errors.
3 rows inserted, 6 values computed.
```python theme={null}
seed_t.collect()
```
## Image Expansion (Outpainting)
Expand an image beyond its original boundaries using `bfl.expand()`.
This is perfect for:
* Making images wider or taller
* Adapting content for different aspect ratios
* Extending scenes naturally
```python theme={null}
# Create a table for image expansion
expand_t = pxt.create_table(
'bfl_demo.expanded',
{'image': pxt.Image, 'expand_prompt': pxt.String},
if_exists='replace',
)
# Add computed column to expand images horizontally
expand_t.add_computed_column(
wide=bfl.expand(
expand_t.expand_prompt,
expand_t.image,
left=256, # Add 256 pixels to left
right=256, # Add 256 pixels to right
)
)
```
Created table 'expanded'.
Added 0 column values with 0 errors.
No rows affected.
```python theme={null}
# Insert an image to expand - using a known small image
expand_t.insert(
image='https://replicate.delivery/pbxt/HtGQBfA5TrqFYZBf0UL18NTqHrzt8UiSIsAkUuMHtjvFDO6p/overture-creations-5sI6fQgYIuo.png',
expand_prompt='Continue the room interior with similar decor and lighting',
)
```
Inserting rows into \`expanded\`: 1 rows \[00:00, 379.78 rows/s]
Inserted 1 row with 0 errors.
1 row inserted, 4 values computed.
```python theme={null}
# View original and expanded images
expand_t.select(expand_t.image, expand_t.wide).show()
```
## Inpainting with Fill
`bfl.fill()` allows you to inpaint specific regions of an image using a
mask:
* **Black areas** in the mask are preserved
* **White areas** in the mask are inpainted based on the prompt
Use cases: remove unwanted objects, replace backgrounds, edit text in
images, restore damaged areas.
```python theme={null}
# Create a table for inpainting
fill_t = pxt.create_table(
'bfl_demo.filled',
{'image': pxt.Image, 'mask': pxt.Image, 'fill_prompt': pxt.String},
if_exists='replace',
)
# Add computed column to fill masked regions
fill_t.add_computed_column(
filled=bfl.fill(
fill_t.fill_prompt,
fill_t.image,
fill_t.mask,
steps=50,
guidance=30,
)
)
```
Created table 'filled'.
Added 0 column values with 0 errors.
No rows affected.
```python theme={null}
# Insert image and mask - the white area in the mask will be inpainted
fill_t.insert(
image='https://replicate.delivery/pbxt/HtGQBfA5TrqFYZBf0UL18NTqHrzt8UiSIsAkUuMHtjvFDO6p/overture-creations-5sI6fQgYIuo.png',
mask='https://replicate.delivery/pbxt/HtGQBqO9MtVbPm0G0K43nsvvjBB0E0PaWOhuNRrRBBT4ttbf/mask.png',
fill_prompt='A fluffy golden retriever sitting on the couch',
)
```
Inserting rows into \`filled\`: 1 rows \[00:00, 531.87 rows/s]
Inserted 1 row with 0 errors.
1 row inserted, 6 values computed.
```python theme={null}
# View original image, mask, and filled result
fill_t.select(fill_t.image, fill_t.mask, fill_t.filled).show()
```
## Best Practices
1. **Use specific prompts**: Include details about style, lighting,
composition, and subject
2. **Start with flux-pro-1.1**: Fast and reliable for most use cases
3. **Use seeds for reproducibility**: When you need consistent results
4. **Resolution**: Minimum 64x64, max 4MP (2048x2048), dimensions must
be multiples of 16
5. **Input image limits**: Max 20MP for editing/expand/fill operations
6. **Safety tolerance**: Default is 2; lower = stricter moderation (0-6
scale)
## Learn More
* [BFL Documentation](https://docs.bfl.ai/)
* [FLUX.2 Overview](https://docs.bfl.ai/flux_2/flux2_overview)
* [Text-to-Image API](https://docs.bfl.ai/flux_2/flux2_text_to_image)
* [Image Editing API](https://docs.bfl.ai/flux_2/flux2_image_editing)
* [Pricing](https://docs.bfl.ai/quick_start/pricing)
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