from dataclasses import dataclass, field
from typing import Dict, List


@dataclass
class IntentClassifier:
    intent_keywords: Dict[str, List[str]] = field(default_factory=lambda:{
        "rag":["document","policy","manual","procedure","hr"],
        "web":["latest","today","news","current","price","stock"],
        "admin":["delete","remove","export","salary","confidential"],
        "general":["explain","summary","help"]
    })
    llm_client: any = None


    async def classify(self, text: str) -> str:
        t = text.lower()
        scores={k:0 for k in self.intent_keywords}
        for k, words in self.intent_keywords.items():
            for w in words:
                if w in t: scores[k]+=1
        best = max(scores, key=scores.get)
        if scores[best] > 0: return best


        # LLM fallback with error handling
        if self.llm_client:
            try:
                prompt=f"Classify into rag/web/admin/general. User: '{text}'"
                out = (await self.llm_client.simple_call(prompt)).strip().lower()
                return out if out in scores else "general"
            except Exception:
                # LLM failed (not configured or unavailable), default to general
                return "general"
        return "general"