"""

  Image embedding encoder using network service.

  Generates embeddings via HTTP API service (default localhost:6005).

  """
  
  import sys
  import os

  import requests

  import numpy as np
  from PIL import Image
  import logging
  import threading

  from typing import List, Optional, Union, Dict, Any

  logger = logging.getLogger(__name__)

  from config.services_config import get_embedding_base_url
  

  
  class CLIPImageEncoder:
      """

      Image Encoder for generating image embeddings using network service.

  
      Thread-safe singleton pattern.
      """
  
      _instance = None
      _lock = threading.Lock()
  

      def __new__(cls, service_url: Optional[str] = None):

          with cls._lock:
              if cls._instance is None:
                  cls._instance = super(CLIPImageEncoder, cls).__new__(cls)

                  resolved_url = service_url or os.getenv("EMBEDDING_SERVICE_URL") or get_embedding_base_url()

                  logger.info(f"Creating CLIPImageEncoder instance with service URL: {resolved_url}")
                  cls._instance.service_url = resolved_url
                  cls._instance.endpoint = f"{resolved_url}/embed/image"

          return cls._instance
  

      def _call_service(self, request_data: List[str]) -> List[Any]:

          """
          Call the embedding service API.

          Args:

              request_data: List of image URLs / local file paths

          Returns:

              List of embeddings (list[float]) or nulls (None), aligned to input order

          """

          try:

              response = requests.post(
                  self.endpoint,
                  json=request_data,
                  timeout=60
              )
              response.raise_for_status()
              return response.json()
          except requests.exceptions.RequestException as e:
              logger.error(f"CLIPImageEncoder service request failed: {e}", exc_info=True)
              raise

  
      def encode_image(self, image: Image.Image) -> Optional[np.ndarray]:

          """
          Encode image to embedding vector using network service.

          Note: This method is kept for compatibility but the service only works with URLs.
          """
          logger.warning("encode_image with PIL Image not supported by service, returning None")
          return None

  
      def encode_image_from_url(self, url: str) -> Optional[np.ndarray]:

          """
          Generate image embedding via network service using URL.

          Args:
              url: Image URL to process

          Returns:
              Embedding vector or None if failed
          """
          try:

              response_data = self._call_service([url])
              if response_data and len(response_data) > 0 and response_data[0] is not None:
                  return np.array(response_data[0], dtype=np.float32)
              logger.warning(f"No embedding for URL {url}")
              return None

  
          except Exception as e:

              logger.error(f"Failed to process image from URL {url}: {str(e)}", exc_info=True)

              return None
  
      def encode_batch(
          self,
          images: List[Union[str, Image.Image]],
          batch_size: int = 8
      ) -> List[Optional[np.ndarray]]:
          """

          Encode a batch of images efficiently via network service.

  
          Args:
              images: List of image URLs or PIL Images

              batch_size: Batch size for processing (used for service requests)

  
          Returns:
              List of embeddings (or None for failed images)
          """

          # Initialize results with None for all images
          results = [None] * len(images)
  
          # Filter out PIL Images since service only supports URLs
          url_images = []
          url_indices = []
  
          for i, img in enumerate(images):
              if isinstance(img, str):
                  url_images.append(img)
                  url_indices.append(i)
              elif isinstance(img, Image.Image):
                  logger.warning(f"PIL Image at index {i} not supported by service, returning None")
                  # results[i] is already None
  
          # Process URLs in batches
          for i in range(0, len(url_images), batch_size):
              batch_urls = url_images[i:i + batch_size]
              batch_indices = url_indices[i:i + batch_size]
  

              try:
                  # Call service

                  response_data = self._call_service(batch_urls)

                  # Process response (aligned list)

                  batch_results = []
                  for j, url in enumerate(batch_urls):

                      if response_data and j < len(response_data) and response_data[j] is not None:
                          batch_results.append(np.array(response_data[j], dtype=np.float32))

                      else:

                          logger.warning(f"Failed to encode URL {url}: no embedding")

                          batch_results.append(None)
  
                  # Insert results at the correct positions
                  for j, result in enumerate(batch_results):
                      results[batch_indices[j]] = result
  
              except Exception as e:
                  logger.error(f"Batch processing failed: {e}", exc_info=True)
                  # Fill with None for this batch
                  for j in range(len(batch_urls)):
                      results[batch_indices[j]] = None

  
          return results

  
      def encode_image_urls(
          self,
          urls: List[str],
          batch_size: Optional[int] = None,
      ) -> List[Optional[np.ndarray]]:
          """
          与 ClipImageModel / ClipAsServiceImageEncoder 一致的接口，供索引器 document_transformer 调用。
  
          Args:
              urls: 图片 URL 列表
              batch_size: 批大小（默认 8）
  
          Returns:
              与 urls 等长的向量列表，失败为 None
          """
          return self.encode_batch(urls, batch_size=batch_size or 8)