AgentCache 2.0: Autonomous Cognitive Infrastructure

The Brain for your AI Agents. AgentCache is no longer just a semantic cache. It is a distributed, self-healing, evolutionary cognitive infrastructure designed to give your AI agents "Systems Thinking" capabilities.

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🧠 Cognitive Architecture

AgentCache implements a Dual-Process Theory engine (System 1 vs System 2), giving your agents reflexes and reasoning.

graph TD
    User[User Query] --> Router{Cognitive Router}
    
    subgraph System 1 [Fast Path < 50ms]
        Router -->|Low Entropy| Synapse[Predictive Synapse]
        Synapse --> Cache[Vector L1 Cache]
        Cache -->|Hit| Response
    end
    
    subgraph System 2 [Slow Path ~10s]
        Router -->|High Entropy| Reasoner[Deep Reasoning]
        Reasoner -->|Chain of Thought| Response
        Reasoner -.->|Skill Compilation| Cache
    end
    
    subgraph Immune System
        Drift[DriftWalker] -->|Heals| Cache
    end
    
    subgraph Hive Mind
        Edge[RosNode Robot] <-->|Federated Sync| Cache
    end

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🚀 Key Capabilities

1. Predictive Synapse (Pre-Cognition)

• What it does: Predicts the user's next query before they type it.
• Math: First-Order Markov Chain with Nucleus Sampling.
• Impact: Enables Negative Latency by pre-fetching probable futures.

2. The Immune System (DriftWalker)

• What it does: Detects "Semantic Rot" in your vector database caused by model updates capabilities drifting.
• Math: Cosine Shift Detection ($1 - Similarity$).
• Impact: Automatically re-embeds and heals decayed memories.

3. Neural Evolution

• What it does: Optimizes your caching strategy (TTL, Eviction, Model routing) using Genetic Algorithms.
• Math: Survival of the Fittest (Fitness = HitRate - Latency).
• Impact: The system "evolves" to fit your specific traffic pattern over generations.

4. The Hive Mind (Federated Robotics)

• What it does: Enables Fleet Learning for edge devices.
• Math: Multi-Modal Vector Embeddings (CLIP/ViT).
• Impact: If Robot A learns to avoid an obstacle, Robot B knows it instantly (Zero-Shot Transfer).

5. Universal Connector (MCP)

• What it does: Exposes the "Brain" to external agents (Cursor, Claude, AutoGPT) via the Model Context Protocol.
• Tools:
  • agentcache_predict_intent: Foresee user intent.
  • agentcache_ask_system2: Engage deep reasoning.
  • agentcache_hive_memory: Access multi-modal memory.

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🛠️ Usage

Quick Start (MCP Server)

# Run the MCP Server to expose tools (Standard IO)
npm run mcp:start

Edge Node (Robotics)

import { RosNode } from 'agentcache-ai/edge';
const robot = new RosNode('worker-01');
// Sensation -> Perception -> Action
const action = await robot.process(sensorData);

Cognitive Router

import { CognitiveRouter } from 'agentcache-ai';
const route = await new CognitiveRouter().route("Design a nuclear reactor");
// Output: 'system_2'

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📦 Installation

npm install agentcache-ai

🧪 Verification

Current System Status: HEALTHY Run the full verification suite to confirm cognitive integrity:

npm run test:verify

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Built with ❤️ by the Neural Engineering Team at AgentCache.