MarkdownTextFilter

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Overview

MarkdownTextFilter transforms Markdown-formatted text into plain text that’s suitable for text-to-speech (TTS) systems. It intelligently removes formatting elements while preserving the content structure, including proper spacing and list formatting.

This filter is especially valuable for LLM-generated content, which often includes Markdown formatting that would sound unnatural if read aloud by a TTS system.

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Constructor

filter = MarkdownTextFilter(params=InputParams())

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Input Parameters

Configure the filter behavior with these options:

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Features

The filter handles these Markdown elements:

• Basic Formatting: Removes *italic*, **bold**, and other formatting markers
• Code: Removes inline code ticks and optionally removes code blocks
• Lists: Preserves numbered lists while removing Markdown formatting
• Tables: Optionally removes Markdown tables
• Whitespace: Carefully preserves meaningful whitespace for natural speech
• HTML: Removes HTML tags and converts entities to their plain text equivalents

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Usage Examples

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Basic Usage with TTS Service

from pipecat.utils.text.markdown_text_filter import MarkdownTextFilter
from pipecat.services.cartesia.tts import CartesiaTTSService

# Create the filter
md_filter = MarkdownTextFilter()

# Use with TTS service
tts = CartesiaTTSService(
    api_key=os.getenv("CARTESIA_API_KEY"),
    voice_id="voice_id_here",
    text_filter=md_filter
)

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Custom Configuration

# Create filter that removes code blocks and tables
md_filter = MarkdownTextFilter(
    params=MarkdownTextFilter.InputParams(
        filter_code=True,
        filter_tables=True
    )
)

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What Gets Removed

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Notes

• Preserves sentence structure and readability
• Maintains whitespace that affects speech prosody
• Handles streaming text with partial Markdown elements
• Efficiently converts HTML entities to plain text characters
• Smart handling of code blocks and tables with state tracking
• Integrates directly with TTS services in the Pipecat pipeline