backend/src/config/__init__.py

from .app_config import get_app_config
from .extensions_config import ExtensionsConfig, get_extensions_config
from .memory_config import MemoryConfig, get_memory_config
from .skills_config import SkillsConfig

__all__ = [
    "get_app_config",
    "SkillsConfig",
    "ExtensionsConfig",
    "get_extensions_config",
    "MemoryConfig",
    "get_memory_config",
]
feat: add config modules 2026-01-14 07:15:58 +08:00			`from .app_config import get_app_config`
feat: add skills api 2026-01-20 13:57:36 +08:00			`from .extensions_config import ExtensionsConfig, get_extensions_config`
feat: add global memory mechanism for personalized conversations Implement a memory system that stores user context and conversation history in memory.json, uses LLM to summarize conversations, and injects relevant context into system prompts for personalized responses. Key components: - MemoryConfig for configuration management - MemoryUpdateQueue with debounce for batch processing - MemoryUpdater for LLM-based memory extraction - MemoryMiddleware to queue conversations after agent execution - Memory injection into lead agent system prompt Note: Add memory section to config.yaml to enable (see config.example.yaml) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> 2026-02-03 13:31:05 +08:00			`from .memory_config import MemoryConfig, get_memory_config`
feat: add skills system for specialized agent workflows (#6) Implement a skills framework that enables specialized workflows for specific tasks (e.g., PDF processing, web page generation). Skills are discovered from the skills/ directory and automatically mounted in sandboxes with path mapping support. - Add SkillsConfig for configuring skills path and container mount point - Implement dynamic skill loading from SKILL.md files with YAML frontmatter - Add path mapping in LocalSandbox to translate container paths to local paths - Mount skills directory in AIO Docker sandbox containers - Update lead agent prompt to dynamically inject available skills - Add setup documentation and expand config.example.yaml Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com> 2026-01-16 14:44:51 +08:00			`from .skills_config import SkillsConfig`
feat: add config modules 2026-01-14 07:15:58 +08:00
feat: add global memory mechanism for personalized conversations Implement a memory system that stores user context and conversation history in memory.json, uses LLM to summarize conversations, and injects relevant context into system prompts for personalized responses. Key components: - MemoryConfig for configuration management - MemoryUpdateQueue with debounce for batch processing - MemoryUpdater for LLM-based memory extraction - MemoryMiddleware to queue conversations after agent execution - Memory injection into lead agent system prompt Note: Add memory section to config.yaml to enable (see config.example.yaml) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> 2026-02-03 13:31:05 +08:00			`__all__ = [`
			`"get_app_config",`
			`"SkillsConfig",`
			`"ExtensionsConfig",`
			`"get_extensions_config",`
			`"MemoryConfig",`
			`"get_memory_config",`
			`]`