"""
Compliance RAG Client — Proxy to Go SDK RAG Search.

Lightweight HTTP client that queries the Go AI Compliance SDK's
POST /sdk/v1/rag/search endpoint. This avoids needing embedding
models or direct Qdrant access in Python.

Error-tolerant: RAG failures never break the calling function.
"""

import logging
import os
from dataclasses import dataclass
from typing import List, Optional

import httpx

logger = logging.getLogger(__name__)

SDK_URL = os.getenv("SDK_URL", "http://ai-compliance-sdk:8090")
RAG_SEARCH_TIMEOUT = 15.0  # seconds


@dataclass
class RAGSearchResult:
    """A single search result from the compliance corpus."""
    text: str
    regulation_code: str
    regulation_name: str
    regulation_short: str
    category: str
    article: str
    paragraph: str
    source_url: str
    score: float
    collection: str = ""


class ComplianceRAGClient:
    """
    RAG client that proxies search requests to the Go SDK.

    Usage:
        client = get_rag_client()
        results = await client.search("DSGVO Art. 35", collection="bp_compliance_recht")
        context_str = client.format_for_prompt(results)
    """

    def __init__(self, base_url: str = SDK_URL):
        self._search_url = f"{base_url}/sdk/v1/rag/search"

    async def search(
        self,
        query: str,
        collection: str = "bp_compliance_ce",
        regulations: Optional[List[str]] = None,
        top_k: int = 5,
    ) -> List[RAGSearchResult]:
        """
        Search the RAG corpus via Go SDK.

        Returns an empty list on any error (never raises).
        """
        payload = {
            "query": query,
            "collection": collection,
            "top_k": top_k,
        }
        if regulations:
            payload["regulations"] = regulations

        try:
            async with httpx.AsyncClient(timeout=RAG_SEARCH_TIMEOUT) as client:
                resp = await client.post(self._search_url, json=payload)

            if resp.status_code != 200:
                logger.warning(
                    "RAG search returned %d: %s", resp.status_code, resp.text[:200]
                )
                return []

            data = resp.json()
            results = []
            for r in data.get("results", []):
                results.append(RAGSearchResult(
                    text=r.get("text", ""),
                    regulation_code=r.get("regulation_code", ""),
                    regulation_name=r.get("regulation_name", ""),
                    regulation_short=r.get("regulation_short", ""),
                    category=r.get("category", ""),
                    article=r.get("article", ""),
                    paragraph=r.get("paragraph", ""),
                    source_url=r.get("source_url", ""),
                    score=r.get("score", 0.0),
                    collection=collection,
                ))
            return results

        except Exception as e:
            logger.warning("RAG search failed: %s", e)
            return []

    async def search_with_rerank(
        self,
        query: str,
        collection: str = "bp_compliance_ce",
        regulations: Optional[List[str]] = None,
        top_k: int = 5,
    ) -> List[RAGSearchResult]:
        """
        Search with optional cross-encoder re-ranking.

        Fetches top_k*4 results from RAG, then re-ranks with cross-encoder
        and returns top_k. Falls back to regular search if reranker is disabled.
        """
        from .reranker import get_reranker

        reranker = get_reranker()
        if reranker is None:
            return await self.search(query, collection, regulations, top_k)

        # Fetch more candidates for re-ranking
        candidates = await self.search(
            query, collection, regulations, top_k=max(top_k * 4, 20)
        )
        if not candidates:
            return []

        texts = [c.text for c in candidates]
        try:
            ranked_indices = reranker.rerank(query, texts, top_k=top_k)
            return [candidates[i] for i in ranked_indices]
        except Exception as e:
            logger.warning("Reranking failed, returning unranked: %s", e)
            return candidates[:top_k]

    async def scroll(
        self,
        collection: str,
        offset: Optional[str] = None,
        limit: int = 100,
    ) -> tuple[List[RAGSearchResult], Optional[str]]:
        """
        Scroll through ALL chunks in a collection (paginated).

        Returns (chunks, next_offset). next_offset is None when done.
        """
        scroll_url = self._search_url.replace("/search", "/scroll")
        params = {"collection": collection, "limit": str(limit)}
        if offset:
            params["offset"] = offset

        try:
            async with httpx.AsyncClient(timeout=30.0) as client:
                resp = await client.get(scroll_url, params=params)

            if resp.status_code != 200:
                logger.warning(
                    "RAG scroll returned %d: %s", resp.status_code, resp.text[:200]
                )
                return [], None

            data = resp.json()
            results = []
            for r in data.get("chunks", []):
                results.append(RAGSearchResult(
                    text=r.get("text", ""),
                    regulation_code=r.get("regulation_code", ""),
                    regulation_name=r.get("regulation_name", ""),
                    regulation_short=r.get("regulation_short", ""),
                    category=r.get("category", ""),
                    article=r.get("article", ""),
                    paragraph=r.get("paragraph", ""),
                    source_url=r.get("source_url", ""),
                    score=0.0,
                    collection=collection,
                ))
            next_offset = data.get("next_offset") or None
            return results, next_offset

        except Exception as e:
            logger.warning("RAG scroll failed: %s", e)
            return [], None

    def format_for_prompt(
        self, results: List[RAGSearchResult], max_results: int = 5
    ) -> str:
        """Format search results as Markdown for inclusion in an LLM prompt."""
        if not results:
            return ""

        lines = ["## Relevanter Rechtskontext\n"]
        for i, r in enumerate(results[:max_results]):
            header = f"{i + 1}. **{r.regulation_short}** ({r.regulation_code})"
            if r.article:
                header += f" — {r.article}"
            lines.append(header)
            text = r.text[:400] + "..." if len(r.text) > 400 else r.text
            lines.append(f"   > {text}\n")

        return "\n".join(lines)


# Singleton
_rag_client: Optional[ComplianceRAGClient] = None


def get_rag_client() -> ComplianceRAGClient:
    """Get the shared RAG client instance."""
    global _rag_client
    if _rag_client is None:
        _rag_client = ComplianceRAGClient()
    return _rag_client