ai

Check if text enhancement is enabled and configured.

Code
Returns
-------
dict
    {"success": True, "enabled": bool, "configured": bool}

Enhance text using AI.

Code
Supports three enhancement modes:
- improve: Transform vague text into clear, actionable content
- simplify: Reduce complexity while keeping core intent
- summarize: Create concise summary of longer text

Parameters
----------
original_text : str, required
    The text to enhance
enhancement_mode : str, required
    The enhancement mode ('improve', 'simplify', or 'summarize')
preset : str, optional
    OpenRouter preset for model selection ('quick', 'balanced', 'quality', etc.)
    If not provided, uses the recommended preset for the enhancement mode.
context : str, optional
    Additional context for the enhancement (e.g., "The intent is to build specs for report creation")

Returns
-------
dict
    On success: {"success": True, "enhancedText": str}
    On error: {"success": False, "error": str}

Get available text enhancement modes.

Code
Returns
-------
dict
    {"success": True, "modes": [{"id": str, "label": str, "description": str}, ...]}

List UW AI analyses for a given revision.

Code
Parameters
----------
revision_id : str, required
    The revision UUID to list analyses for.

Returns
-------
dict
    On success: {"success": True, "analyses": [...]}
    On error: {"success": False, "error": str}

Validate a user-submitted AI Analysis prompt for safety and relevance.

Code
Uses an LLM to determine whether the prompt is safe (no injection) and
relevant to the available underwriting data context.

Parameters
----------
prompt : str, required
    The analysis prompt text to validate.
category_scope : str, required
    The rule's category scope (e.g. 'policy', 'vehicle').

Returns
-------
dict
    {"success": True, "valid": bool, "reason": str}