"""Implement cross-encoder reranking via an OpenAI-compatible reranker API."""

from __future__ import annotations

import time

import requests
from loguru import logger

from app.config.settings import settings
from app.domain.retrieval import Reranker, RetrievedChunk


class OpenAICompatibleReranker(Reranker):
    """Call a TEI / Cohere-style reranker endpoint to re-score retrieved chunks."""

    def __init__(
        self,
        base_url: str | None = None,
        model: str | None = None,
        api_key: str | None = None,
        timeout: int = 30,
    ) -> None:
        self._base_url = (base_url or settings.reranker_base_url).rstrip("/")
        self._model = model or settings.reranker_model
        self._api_key = api_key or settings.reranker_api_key
        self._timeout = timeout

    def rerank(self, query: str, chunks: list[RetrievedChunk], top_k: int) -> list[RetrievedChunk]:
        """Return up to top_k chunks re-sorted by cross-encoder score."""
        if not chunks:
            return []

        texts = [chunk.content for chunk in chunks]
        start = time.time()
        try:
            scores = self._call_reranker(query, texts)
        except Exception as exc:
            logger.warning("Reranker call failed ({}), falling back to original order: {}", type(exc).__name__, exc)
            return chunks[:top_k]

        elapsed_ms = int((time.time() - start) * 1000)
        logger.debug("Reranker scored {} chunks in {}ms", len(chunks), elapsed_ms)

        ranked = sorted(
            [(score, chunk) for score, chunk in zip(scores, chunks)],
            key=lambda x: x[0],
            reverse=True,
        )
        result = []
        for score, chunk in ranked[:top_k]:
            chunk.score = float(score)
            result.append(chunk)
        return result

    def _call_reranker(self, query: str, texts: list[str]) -> list[float]:
        """Call the reranker API and return a score per text."""
        headers = {"Content-Type": "application/json"}
        if self._api_key:
            headers["Authorization"] = f"Bearer {self._api_key}"

        # Try TEI format first: POST /rerank
        payload = {"query": query, "texts": texts, "raw_scores": False, "return_text": False}
        url = f"{self._base_url}/rerank"
        resp = requests.post(url, json=payload, headers=headers, timeout=self._timeout)

        if resp.status_code == 404:
            # Fall back to Cohere / OpenAI-style: POST /v1/rerank
            payload_v1 = {"model": self._model, "query": query, "documents": texts}
            url = f"{self._base_url}/v1/rerank"
            resp = requests.post(url, json=payload_v1, headers=headers, timeout=self._timeout)

        resp.raise_for_status()
        data = resp.json()

        # TEI response: list of {"index": N, "score": F}
        if isinstance(data, list):
            ordered = sorted(data, key=lambda x: x["index"])
            return [float(item["score"]) for item in ordered]

        # Cohere/OpenAI response: {"results": [{"index": N, "relevance_score": F}]}
        results = data.get("results", [])
        ordered = sorted(results, key=lambda x: x["index"])
        return [float(item.get("relevance_score", item.get("score", 0))) for item in ordered]