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airunner.api

This directory contains the core API service layer for the AI Runner application. It provides a modular, signal-based interface for interacting with various AI and multimedia services, decoupling business logic from the GUI and application lifecycle.

Overview

  • api.py: Main singleton API class, tightly integrated with the application and GUI. Use this when you need full app and signal integration.
  • api_manager.py: Lightweight, decoupled manager for API services. Use this in headless, worker, or test contexts where GUI/app logic is not needed.
  • api_service_base.py: Base class for all API services, providing signal emission and settings integration.

Service Modules

Each service module provides a class for interacting with a specific domain via signals:

  • art_services.py: Stable Diffusion and image generation workflows.
  • canvas_services.py: Canvas/grid/image editing and manipulation.
  • chatbot_services.py: Chatbot mood and interaction signals.
  • embedding_services.py: Embedding management and status updates.
  • image_filter_services.py: Image filter application and preview.
  • llm_services.py: Large Language Model (LLM) requests, chat, and RAG operations.
  • lora_services.py: LoRA (Low-Rank Adaptation) model management.
  • stt_services.py: Speech-to-text (STT) processing.
  • tts_services.py: Text-to-speech (TTS) playback and control.
  • video_services.py: Video generation and progress updates.

Testing

Unit tests for all services are provided in the test/ subdirectory. These use pytest and unittest.mock to verify signal emission and service logic.