frontend/services/apiService.ts

import type { Dataset, DataItem, Modality, SingleComparisonResult, DatasetMetadata } from '../types';

// Define the base URL for your backend API
// For local development, it might be 'http://localhost:8000'
// When deployed on Hugging Face Spaces, it will be a relative path '/'.
const API_BASE_URL = '/'; 

/**
 * A helper function to handle API errors.
 */
const handleApiError = async (response: Response) => {
  if (!response.ok) {
    let errorMessage = `HTTP error! status: ${response.status}`;
    try {
      const errorData = await response.json();
      errorMessage = errorData.detail || JSON.stringify(errorData);
    } catch (e) {
      // The response was not JSON
      errorMessage = await response.text();
    }
    throw new Error(errorMessage);
  }
  return response.json();
};

// Helper to correctly encode unicode strings to base64, which is required by the backend.
const unicodeToBase64 = (str: string) => {
    return btoa(
        encodeURIComponent(str).replace(/%([0-9A-F]{2})/g, (match, p1) => {
            return String.fromCharCode(parseInt(p1, 16));
        })
    );
};


const contentToBase64 = (content: string | ArrayBuffer, modality: Modality): Promise<string> => {
    return new Promise((resolve, reject) => {
        if (modality === 'text') {
            try {
                // Use helper for proper unicode support
                resolve(unicodeToBase64(content as string));
            } catch (error) {
                console.error("Failed to Base64 encode text content:", error);
                reject(new Error("Failed to encode text. Ensure it doesn't contain unsupported characters."));
            }
        } else if (typeof content === 'string') {
            // For images, content is a data URL
            const parts = content.split(',');
            resolve(parts.length > 1 ? parts[1] : content);
        } else if (content instanceof ArrayBuffer) {
            // For meshes
            const bytes = new Uint8Array(content);
            let binary = '';
            for (let i = 0; i < bytes.byteLength; i++) {
                binary += String.fromCharCode(bytes[i]);
            }
            resolve(btoa(binary));
        } else {
            reject(new Error('Unsupported content type for base64 conversion.'));
        }
    });
};

/**
 * Post-processes data received from the backend to ensure correct frontend rendering.
 * - Converts raw Base64 image strings to Data URLs.
 * - Converts raw Base64 mesh strings to ArrayBuffers.
 */
const postProcessApiData = <T extends { content: string | ArrayBuffer }>(item: T, modality: 'images' | 'texts' | 'meshes'): T => {
    if (modality === 'images' && typeof item.content === 'string' && !item.content.startsWith('data:')) {
        item.content = `data:image/png;base64,${item.content}`;
    }
    if (modality === 'meshes' && typeof item.content === 'string') {
        const binaryString = atob(item.content);
        const len = binaryString.length;
        const bytes = new Uint8Array(len);
        for (let i = 0; i < len; i++) {
            bytes[i] = binaryString.charCodeAt(i);
        }
        item.content = bytes.buffer;
    }
    return item;
}

/**
 * Starts the dataset processing on the backend by uploading a .zip file.
 * @param file The .zip file to upload.
 * @returns A promise that resolves with a job ID for polling the status.
 */
export const startDatasetProcessing = async (file: File): Promise<string> => {
  const formData = new FormData();
  formData.append('file', file);

  const response = await fetch(`${API_BASE_URL}api/process-dataset`, {
    method: 'POST',
    body: formData,
  });

  const { job_id } = await handleApiError(response);
  if (!job_id) {
    throw new Error("API did not return a job ID.");
  }
  return job_id;
};


interface ProcessingStatus {
    status: 'starting' | 'processing' | 'complete' | 'error';
    stage?: string;
    progress?: number;
    message?: string;
    result?: Dataset;
}

/**
 * Polls the backend for the status of a dataset processing job.
 * @param jobId The ID of the job to check.
 * @returns A promise that resolves with the current status.
 */
export const getProcessingStatus = async (jobId: string): Promise<ProcessingStatus> => {
    const response = await fetch(`${API_BASE_URL}api/processing-status/${jobId}`);
    const status: ProcessingStatus = await handleApiError(response);
    
    // If the job is complete, post-process the resulting dataset data
    if (status.status === 'complete' && status.result) {
        const processedDataset = status.result;
        // The backend returns a string for the date, convert it to a Date object.
        if (processedDataset.uploadDate && typeof processedDataset.uploadDate === 'string') {
            processedDataset.uploadDate = new Date(processedDataset.uploadDate);
        }

        // Ensure all data items have the correct format for frontend rendering.
        if (processedDataset.data) {
            if (processedDataset.data.images) {
                processedDataset.data.images = processedDataset.data.images.map((item: DataItem) => postProcessApiData(item, 'images'));
            }
            if (processedDataset.data.meshes) {
                processedDataset.data.meshes = processedDataset.data.meshes.map((item: DataItem) => postProcessApiData(item, 'meshes'));
            }
        }
        status.result = processedDataset;
    }
    
    return status;
}

/**
 * Sends a local dataset to the backend to populate its in-memory cache.
 * This is crucial for making comparisons after a page reload.
 * @param dataset The full local dataset object from IndexedDB.
 */
export const ensureDatasetInCache = async (dataset: Dataset): Promise<void> => {
    // The backend expects content as base64 or raw text, but our Mesh content is an ArrayBuffer.
    // We need to convert it before sending. Images are already data URLs (string).
    const payload = {
        ...dataset,
        data: {
            ...dataset.data,
            meshes: await Promise.all(dataset.data.meshes.map(async (mesh) => {
                if (mesh.content instanceof ArrayBuffer) {
                    return { ...mesh, content: await contentToBase64(mesh.content, 'mesh') };
                }
                return mesh;
            })),
        }
    };

    const response = await fetch(`${API_BASE_URL}api/cache-local-dataset`, {
        method: 'POST',
        headers: { 'Content-Type': 'application/json' },
        body: JSON.stringify(payload),
    });

    await handleApiError(response);
};

/**
 * Finds the top matches for a single item by querying the backend.
 * @param sourceItem The item to find matches for.
 * @param sourceModality The modality of the source item.
 * @param datasetId The ID of the dataset to search within.
 * @returns A promise that resolves with the comparison results.
 */
export const findTopMatches = async (
  sourceItem: DataItem,
  sourceModality: Modality,
  datasetId: string
): Promise<SingleComparisonResult> => {

  const contentAsBase64 = await contentToBase64(sourceItem.content, sourceModality);
  
  const requestBody = {
    modality: sourceModality,
    content: contentAsBase64,
    dataset_id: datasetId,
  };

  const response = await fetch(`${API_BASE_URL}api/find-matches`, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify(requestBody),
  });

  const result: SingleComparisonResult = await handleApiError(response);
  
  // The API returns a representation of the source item with raw base64.
  // We replace it with our original source item which has the correct format for rendering.
  result.sourceItem = sourceItem;

  // Post-process all returned match items to ensure they render correctly.
  for (const key of Object.keys(result.results)) {
      const modalityKey = key as 'images' | 'texts' | 'meshes';
      const matches = result.results[modalityKey];
      if (matches) {
          matches.forEach(match => {
              postProcessApiData(match.item, modalityKey);
          });
      }
  }

  return result;
};


// --- Service functions for SHARED datasets ---

/**
 * Returns the metadata for all available shared datasets by querying the backend.
 */
export const getSharedDatasetMetadata = async (): Promise<DatasetMetadata[]> => {
  try {
    const response = await fetch('/api/shared-dataset-metadata');
    const metadataList = await handleApiError(response);
    
    // The backend returns strings for dates, convert them to Date objects.
    return metadataList.map((meta: any) => ({
        ...meta,
        uploadDate: new Date(meta.uploadDate),
    }));
  } catch (error) {
    console.error("Failed to fetch shared dataset metadata:", error);
    // Re-throw the error so the UI layer can handle it.
    throw error;
  }
};

/**
 * Returns the full data structure for a specific shared dataset from the backend.
 * The content for each item remains null, only the URLs are provided.
 */
export const getSharedDataset = async (id: string): Promise<Dataset | null> => {
  try {
    const response = await fetch(`/api/shared-dataset?id=${id}`);
    const dataset = await handleApiError(response);
    
    // Convert date string from API to Date object
    dataset.uploadDate = new Date(dataset.uploadDate);
    
    return dataset;
  } catch (error) {
    console.error(`Failed to fetch shared dataset with id ${id}:`, error);
    // Re-throw the error so the UI layer can handle it.
    throw error;
  }
};