# Memory Management Specification ## ADDED Requirements ### Requirement: Model Manager The system SHALL provide a ModelManager class that manages model lifecycle with reference counting and idle timeout mechanisms. #### Scenario: Loading a model GIVEN a request to load a model WHEN the model is not already loaded THEN the ModelManager creates a new instance and sets reference count to 1 #### Scenario: Reusing loaded model GIVEN a model is already loaded WHEN another request for the same model arrives THEN the ModelManager returns the existing instance and increments reference count #### Scenario: Unloading idle model GIVEN a model with zero reference count WHEN the idle timeout period expires THEN the ModelManager unloads the model and frees memory ### Requirement: Service Pool The system SHALL implement an OCRServicePool that manages a pool of OCRService instances with one instance per GPU/CPU device. #### Scenario: Acquiring service from pool GIVEN a task needs processing WHEN a service is requested from the pool THEN the pool returns an available service or queues the request if all services are busy #### Scenario: Releasing service to pool GIVEN a task has completed processing WHEN the service is released THEN the service becomes available for other tasks in the pool ### Requirement: Memory Monitoring The system SHALL continuously monitor GPU and CPU memory usage and trigger preventive actions based on configurable thresholds. #### Scenario: Memory warning threshold GIVEN memory usage reaches 80% (warning threshold) WHEN a new task is requested THEN the system logs a warning and may defer non-critical operations #### Scenario: Memory critical threshold GIVEN memory usage reaches 95% (critical threshold) WHEN a new task is requested THEN the system attempts CPU fallback or rejects the task ### Requirement: Concurrency Control The system SHALL limit concurrent PP-StructureV3 predictions using semaphores to prevent memory exhaustion. #### Scenario: Concurrent prediction limit GIVEN the maximum concurrent predictions is set to 2 WHEN 2 predictions are already running THEN additional prediction requests wait in queue until a slot becomes available ### Requirement: Resource Cleanup The system SHALL ensure all resources are properly cleaned up after task completion or failure. #### Scenario: Successful task cleanup GIVEN a task completes successfully WHEN the task finishes THEN all allocated memory, temporary files, and model references are released #### Scenario: Failed task cleanup GIVEN a task fails with an error WHEN the error handler runs THEN cleanup is performed in the finally block regardless of failure reason ## MODIFIED Requirements ### Requirement: OCR Service Instantiation The OCR service instantiation SHALL use pooled instances instead of creating new instances for each task. #### Scenario: Task using pooled service GIVEN a new OCR task arrives WHEN the task starts processing THEN it acquires a service from the pool instead of creating a new instance ### Requirement: PP-StructureV3 Model Management The PP-StructureV3 model SHALL be subject to the same lifecycle management as other models, removing its permanent exemption from unloading. #### Scenario: PP-StructureV3 unloading GIVEN PP-StructureV3 has been idle for the configured timeout WHEN memory pressure is detected THEN the model can be unloaded to free memory ### Requirement: Task Resource Tracking Tasks SHALL track their resource usage including estimated and actual memory consumption. #### Scenario: Task memory tracking GIVEN a task is processing WHEN memory metrics are collected THEN the task records both estimated and actual memory usage for analysis ## REMOVED Requirements ### Requirement: Permanent Model Loading The requirement for PP-StructureV3 to remain permanently loaded SHALL be removed. #### Scenario: Dynamic model loading GIVEN the system starts WHEN no tasks are using PP-StructureV3 THEN the model is not loaded until first use