app_analysis.py

# app_analysis.py
from flask import Blueprint, jsonify, request
import uuid
import logging

# Import configuration from the main config.py
from config import NUM_RECENT_ALBUMS, TOP_N_MOODS

# RQ import
from rq import Retry

logger = logging.getLogger(__name__)

# Create a Blueprint for analysis-related routes
analysis_bp = Blueprint('analysis_bp', __name__)

@analysis_bp.route('/cleaning', methods=['GET'])
def cleaning_page():
    """
    Serves the HTML page for the Database Cleaning feature.
    ---
    tags:
      - UI
    responses:
      200:
        description: HTML content of the cleaning page.
        content:
          text/html:
            schema:
              type: string
    """
    from flask import render_template
    return render_template('cleaning.html', title = 'AudioMuse-AI - Database Cleaning', active='cleaning')

@analysis_bp.route('/api/analysis/start', methods=['POST'])
def start_analysis_endpoint():
    """
    Start the music analysis process for recent albums.
    This endpoint enqueues a main analysis task.
    Note: Starting a new analysis task will archive previously successful tasks by setting their status to REVOKED.
    ---
    tags:
      - Analysis
    requestBody:
      description: Configuration for the analysis task.
      required: false
      content:
        application/json:
          schema:
            type: object
            properties:
              num_recent_albums:
                type: integer
                description: Number of recent albums to process.
                default: "Configured NUM_RECENT_ALBUMS"
              top_n_moods:
                type: integer
                description: Number of top moods to extract per track.
                default: "Configured TOP_N_MOODS"
    responses:
      202:
        description: Analysis task successfully enqueued.
        content:
          application/json:
            schema:
              type: object
              properties:
                task_id:
                  type: string
                  description: The ID of the enqueued main analysis task.
                task_type:
                  type: string
                  description: Type of the task (e.g., main_analysis).
                  example: main_analysis
                status:
                  type: string
                  description: The initial status of the job in the queue (e.g., queued).
      400:
        description: Invalid input.
      500:
        description: Server error during task enqueue.
    """
    # Local imports to prevent circular dependency at startup
    from app_helper import rq_queue_high, clean_up_previous_main_tasks, save_task_status, TASK_STATUS_PENDING

    data = request.json or {}
    # MODIFIED: Removed jellyfin_url, jellyfin_user_id, and jellyfin_token as they are no longer passed to the task.
    # The task now gets these details from the central config.
    num_recent_albums = int(data.get('num_recent_albums', NUM_RECENT_ALBUMS))
    top_n_moods = int(data.get('top_n_moods', TOP_N_MOODS))
    logger.info(f"Starting analysis request: num_recent_albums={num_recent_albums}, top_n_moods={top_n_moods}")

    job_id = str(uuid.uuid4())

    # Clean up details of previously successful or stale tasks before starting a new one
    clean_up_previous_main_tasks()
    save_task_status(job_id, "main_analysis", TASK_STATUS_PENDING, details={"message": "Task enqueued."})

    # Enqueue task using a string path to its function.
    # MODIFIED: The arguments passed to the task are updated to match the new function signature.
    job = rq_queue_high.enqueue(
        'tasks.analysis.run_analysis_task',
        args=(num_recent_albums, top_n_moods),
        job_id=job_id,
        description="Main Music Analysis",
        retry=Retry(max=3),
        job_timeout=-1 # No timeout
    )
    return jsonify({"task_id": job.id, "task_type": "main_analysis", "status": job.get_status()}), 202

@analysis_bp.route('/api/cleaning/start', methods=['POST'])
def start_cleaning_endpoint():
    """
    Identify and automatically clean orphaned albums from the database.
    This endpoint enqueues a cleaning task that both identifies and deletes orphaned albums.
    ---
    tags:
      - Cleaning
    responses:
      202:
        description: Database cleaning task successfully enqueued.
        content:
          application/json:
            schema:
              type: object
              properties:
                task_id:
                  type: string
                  description: The ID of the enqueued database cleaning task.
                task_type:
                  type: string
                  description: Type of the task (cleaning).
                  example: cleaning
                status:
                  type: string
                  description: The initial status of the job in the queue (e.g., queued).
      500:
        description: Server error during task enqueue.
    """
    # Local imports to prevent circular dependency at startup
    from app_helper import rq_queue_high, clean_up_previous_main_tasks, save_task_status, TASK_STATUS_PENDING

    # Clean up any previous cleaning tasks
    clean_up_previous_main_tasks()

    job_id = str(uuid.uuid4())
    save_task_status(job_id, "cleaning", TASK_STATUS_PENDING, details={"message": "Database cleaning task enqueued."})

    # Enqueue combined cleaning task
    job = rq_queue_high.enqueue(
        'tasks.cleaning.identify_and_clean_orphaned_albums_task',
        job_id=job_id,
        description="Database Cleaning (Identify and Delete Orphaned Albums)",
        retry=Retry(max=2),
        job_timeout=-1 # No timeout
    )
    return jsonify({"task_id": job.id, "task_type": "cleaning", "status": job.get_status()}), 202