The Ultimate Guide to Formatting AI Chat Outputs: Master Regex for Roleplay

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You spend hours crafting the perfect character lore, configuring your API parameters, and writing a brilliant opening message. The AI generates a highly intelligent response, but the formatting is completely broken. Dialogue is missing quotes, actions are bracketed instead of asterisked, and the bot insists on starting every message with Assistant:.

Immersion shatters immediately.

Relying on system prompts to dictate formatting is a losing battle. Large Language Models suffer from formatting drift. As the context window fills up, the model reverts to the raw markdown structures from its training data. Attempting to fix this by screaming "USE ASTERISKS FOR ACTIONS" in your Creator Notes wastes valuable context tokens and rarely works permanently.

Guaranteeing consistent output formatting requires hardcoded structural rules. You need Regex (Regular Expressions).

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1. The Anatomy of Regex in AI Roleplay

Regex is a sequence of characters that specifies a search pattern. In the context of AI frontends, it functions as a microscopic find-and-replace engine. It scans the incoming text stream from the LLM, identifies specific structural patterns, and rewrites them in real-time.

To manipulate chat outputs, you only need to understand three core components:

• Literal Characters: The exact text you want to find (e.g., *, ", AI:).
• Wildcards and Quantifiers: Symbols that represent variable text. . means "any character," and * means "zero or more times." Therefore, .* translates to "literally anything."
• Capture Groups: Wrapping a section of your regex in parentheses () saves the text found inside that specific pattern so you can reuse it in the replacement string (referred to as $1, $2, etc.).

[Image Prompt: A high-contrast, black and white minimalist photograph of parallel steel rails converging perfectly into a vanishing point, representing rigid alignment and structure.]

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2. Essential Regex Snippets (Copy & Paste)

These are the foundational Regex scripts every roleplayer should implement in their frontend client to sanitize raw API outputs.

Fix 1: Forcing Italics on Asterisk Actions

Many uncensored models output actions wrapped in asterisks (e.g., *smiles*) but fail to trigger the markdown italicization in certain frontends. This script captures everything between asterisks and forces HTML italics.

• Target Pattern: \*([^*]+)\*
• Replacement: <i>$1</i>

How it works: The \* looks for a literal asterisk. The ([^*]+) is a capture group that grabs every character until it hits the next asterisk. The replacement wraps that captured text ($1) in standard HTML tags.

Fix 2: Stripping Annoying AI Prefixes

Models trained on ChatML or Alpaca datasets often hallucinate their conversational roles, leading to outputs that start with Character: or AI:. This script aggressively removes them.

• Target Pattern: ^(?:Character|AI|Assistant):\s*
• Replacement: (Leave blank)

How it works: The ^ asserts the start of the line. The (?:...) looks for specific words. The \s* catches any trailing spaces. Replacing it with nothing deletes the prefix entirely, leaving only the actual dialogue.

Fix 3: Standardizing Dialogue Quotes

If an AI mixes up standard quotes " " with directional quotes “ ” or foreign brackets 「 」, you can force uniformity.

• Target Pattern: [“”「」]
• Replacement: "

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3. Native Formatting vs. Custom Control

While Regex is powerful, writing and maintaining a massive library of scripts for every minor model quirk is exhausting. You shouldn't need a background in computer science just to force an AI to use italics properly.

This friction between user control and technical fatigue was a primary focus when developing Abolitus.

Instead of forcing users to build their formatting rules from scratch, Abolitus handles output formatting through a dual-tier architecture:

• Tier 1: Native Roleplay Formatting: Out of the box, Abolitus natively understands standard roleplay syntax. Basic formatting—like italicizing asterisk-bound actions or standardizing quotation marks—is built directly into the client engine. You get perfectly formatted, readable output on day one without touching a single line of code.
• Tier 2: The Advanced Regex Engine: For power users pushing specific aesthetics or dealing with highly experimental local models, Abolitus provides a robust, fully customizable Regex interface.

Because Abolitus is a true local-first client, your custom rules execute strictly via Client-Side Processing. Drop your custom scripts into the UI, and your browser's CPU handles the text replacement instantly as the text streams in from your OpenRouter or Ollama endpoint. No server-side latency, no formatting lag.

Stop fighting the model's hallucinations. Rely on native formatting for the basics, deploy custom rules for the edge cases, and lock down your aesthetic. Try Abolitus today and take total control of your output.