Memfit AI breaks through the limitations of single paradigms by innovatively adopting a Recursive Coupling of ReAct and Plan-Execute hybrid architecture. This architecture organically fuses macroscopic Strategic Planning with microscopic Tactical Execution through a Coordinator, achieving a unity of determinism and flexibility in task processing.
| Engine | Layer | Responsibility |
|---|---|---|
| Plan Engine | Strategic | Macroscopic deconstruction of tasks into structured Task Trees with temporal dependencies and logical associations |
| ReAct Engine | Tactical | Dynamic execution of atomic tasks through "Observation - Thought - Action" closed loops |
Recursive Coupling Mechanism: When the ReAct engine encounters complex sub-problems, it dynamically triggers the Plan engine for Sub-planning. This recursive mechanism supports fractal expansion of tasks, adapting to business scenarios of arbitrary complexity.
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Coordinator Entry (Plan-Execute Mode)
- For vague or complex tasks
- Flow:
User → Coordinator → Planning Loop → Review → Runtime → ReAct Loops
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ReAct Entry (Instant Execution Mode)
- For clear, atomic instructions
- Flow:
User → ReAct Loop → Thought → Action → Observation
- Coordinator - System bus and lifecycle manager
- ReActLoop - Minimal execution unit with "Reasoning-Acting" cycle
- Tools & Forges - Standardized atomic capabilities and scenario-based AI Blueprints
- Memory Triage - Intelligent long-term memory using C.O.R.E. P.A.C.T. Framework
- RAG System - Active, agentic knowledge service with hybrid indexing
- Self-Reflection - Analyzes failures and generates correction plans
- Spin Detection - Prevents infinite loops in actions or logic
- Memory-Augmented Recovery - Retrieves historical error cases for decision support
- Full Documentation
- Yaklang - The underlying language powering Memfit AI
- SSA Analysis - Static Single Assignment analysis platform
Memfit AI 突破了单一范式的局限,创新性地采用了 ReAct 与 Plan-Execute 递归耦合 的混合架构。该架构通过 Coordinator(协调器)将宏观的 战略规划 与微观的 战术执行 有机融合,实现了任务处理中确定性与灵活性的统一。
| 引擎 | 层级 | 职责 |
|---|---|---|
| Plan 引擎 | 战略层 | 将顶层目标拆解为具备时序依赖与逻辑关联的结构化 任务树 |
| ReAct 引擎 | 战术层 | 通过 "观察 - 推理 - 行动" 的闭环机制动态执行原子任务 |
递归耦合机制: 当 ReAct 引擎遇到复杂子问题时,可动态触发 Plan 引擎进行 次级规划。这种递归调用机制支持任务的分形扩展,可适应任意复杂度的业务场景。
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Coordinator 入口 (Plan-Execute 模式)
- 适用于模糊或复杂的任务
- 流程:
用户 → Coordinator → 规划循环 → 审查 → 运行时 → ReAct Loops
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ReAct 入口 (即时执行模式)
- 适用于明确的原子化指令
- 流程:
用户 → ReAct Loop → 思考 → 行动 → 观察
- Coordinator - 系统总线与生命周期管理器
- ReActLoop - 最小执行单元,驱动 "Reasoning-Acting" 循环
- Tools & Forges - 标准化原子能力与场景化 AI 蓝图
- Memory Triage - 基于 C.O.R.E. P.A.C.T. 框架的智能长期记忆
- RAG System - 主动式代理化知识服务,支持混合索引
- 自我反思 - 分析失败原因并生成修正计划
- 自旋检测 - 防止动作或逻辑死循环
- 记忆增强恢复 - 检索历史相似错误案例辅助决策
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