#!/usr/bin/env python3
"""
Budgetary Sovereign Router — Complexity-Aware Inference Steering.

Uses a deterministic GOFAI scoring model to determine if a prompt 
requires high-reasoning (Cloud LLM) or commodity-reasoning (Local LLM).
"""

import re
import logging
from typing import List, Dict, Any
from tools.registry import registry, tool_error, tool_result

logger = logging.getLogger(__name__)

ROUTER_SCHEMA = {
    "name": "sovereign_router",
    "description": "Analyzes a prompt and recommends the most cost-effective inference path. It uses a GOFAI model to detect complexity markers, potentially saving 90% in cloud costs for 'Small Fry' operations.",
    "parameters": {
        "type": "object",
        "properties": {
            "prompt": {"type": "string", "description": "The prompt or task description to analyze."}
        },
        "required": ["prompt"]
    }
}

class ComplexityScore:
    HIGH_REASONING_MARKERS = [
        r"refactor", r"architect", r"design pattern", r"security audit", 
        r"complex", r"debug a crash", r"optimize performance"
    ]
    COMMODITY_MARKERS = [
        r"summarize", r"extract json", r"clean up typos", r"format", 
        r"write a test for", r"todo", r"explain"
    ]

    @classmethod
    def score(cls, text: str) -> int:
        score = 0
        text = text.lower()
        for marker in cls.HIGH_REASONING_MARKERS:
            if re.search(marker, text):
                score += 5
        for marker in cls.COMMODITY_MARKERS:
            if re.search(marker, text):
                score -= 3
        # Length penalty
        if len(text) > 2000:
            score += 2
        return score

def route_prompt(prompt: str):
    """Determine routing path."""
    score = ComplexityScore.score(prompt)
    
    threshold = 2
    recommendation = "CLOUD" if score >= threshold else "LOCAL"
    
    return tool_result(
        status="Routing Determined",
        score=score,
        recommendation=recommendation,
        reason=f"Prompt complexity score is {score}. Threshold for Cloud is {threshold}.",
        action=f"Routing this request to ${recommendation} inference engine."
    )

def _handle_router(args, **kwargs):
    return route_prompt(args.get("prompt"))

registry.register(
    name="sovereign_router",
    toolset="dispatch",
    schema=ROUTER_SCHEMA,
    handler=_handle_router,
    emoji="🚦"
)