Enumerations

Component type definitions and registry for the streamlit_rich_message_history package.

This module defines the core component types and provides a registry system for extending the package with custom component types, detectors, and renderers.

class streamlit_rich_message_history.enums.ComponentRegistry

Bases: object

Registry to manage custom component types, detectors, and renderers.

This class provides static methods for registering and retrieving: - Custom component types (extending ComponentType) - Type detection functions that identify content types - Rendering functions that display specific content types

The registry is a central point for extending the package with custom components.

classmethod get_all_types()

Get all component types (built-in and custom).

Returns:

List containing all ComponentType values

Return type:

list

classmethod get_custom_type(name)

Get a custom component type by name.

Parameters:

name (str) – String identifier of the component type

Returns:

The component type if found, None otherwise

Return type:

ComponentType

classmethod get_detector(comp_type)

Get the detector function for a component type.

Parameters:

comp_type (ComponentType) – The component type to get the detector for

Returns:

The detector function if registered, None otherwise

Return type:

Callable

classmethod get_renderer(comp_type)

Get the renderer function for a component type.

Parameters:

comp_type (ComponentType) – The component type to get the renderer for

Returns:

The renderer function if registered, None otherwise

Return type:

Callable

classmethod register_component_type(name)

Register a new component type with the given name. If a component type with this name already exists, returns the existing type with a warning instead of raising an exception.

Parameters:

name (str) – String identifier for the new component type

Returns:

The newly created component type or existing component type

Return type:

ComponentType

Examples

>>> IMAGE_TYPE = ComponentRegistry.register_component_type("image")
>>> # IMAGE_TYPE can now be used like a standard ComponentType
>>> # Registering the same type again will return the existing type
>>> SAME_IMAGE_TYPE = ComponentRegistry.register_component_type("image")
>>> # A warning will be printed and SAME_IMAGE_TYPE == IMAGE_TYPE

classmethod register_detector(comp_type, detector)

Register a detector function for a component type.

The detector function determines if content should be treated as this component type.

Parameters:

• comp_type (ComponentType) – The component type to register a detector for

• detector (Callable[[Any, Dict[str, Any]], bool]) – Function that takes content and kwargs and returns True if the content should be handled as this component type

Return type:

None

Examples

>>> def image_detector(content, kwargs):
        return isinstance(content, PIL.Image.Image)
>>> ComponentRegistry.register_detector(IMAGE_TYPE, image_detector)

classmethod register_renderer(comp_type, renderer)

Register a renderer function for a component type.

The renderer function handles displaying the content in a Streamlit app.

Parameters:

• comp_type (ComponentType) – The component type to register a renderer for

• renderer (Callable[[Any, Dict[str, Any]], None]) – Function that takes content and kwargs and renders it in Streamlit

Return type:

None

Examples

>>> def image_renderer(content, kwargs):
        st.image(content, **{k: v for k, v in kwargs.items()
                         if k in ['caption', 'width', 'use_column_width']})
>>> ComponentRegistry.register_renderer(IMAGE_TYPE, image_renderer)

class streamlit_rich_message_history.enums.ComponentType(value)

Bases: Enum

Enum defining the possible message component types.

These types correspond to different ways content can be displayed in messages, such as text, dataframes, charts, etc.

TEXT

Plain text content

DATAFRAME

Pandas DataFrame display

SERIES

Pandas Series display

MATPLOTLIB_FIGURE

Matplotlib plot

PLOTLY_FIGURE

Plotly chart

NUMBER

Numeric value

ERROR

Error message

CODE

Code snippet with syntax highlighting

METRIC

Metric with optional delta

TABLE

Static table display

JSON

JSON data viewer

HTML

HTML content

LIST

List of items

TUPLE

Tuple of items

DICT

Dictionary of items

CODE = 'code'

DATAFRAME = 'dataframe'

DICT = 'dict'

ERROR = 'error'

HTML = 'html'

JSON = 'json'

LIST = 'list'

MATPLOTLIB_FIGURE = 'matplotlib_figure'

METRIC = 'metric'

NUMBER = 'number'

PLOTLY_FIGURE = 'plotly_figure'

SERIES = 'series'

TABLE = 'table'

TEXT = 'text'

TUPLE = 'tuple'