---
title: Features
description: Detailed feature behavior for the AI extension and its related packages
deprecated: true
supersededBy: ['/docs/cortex', '/docs/shield', '/docs/sentinel', '/docs/weave', '/docs/nexus']
---

## Core Extension Features

### 1. Container-Managed AI Service Graph

On `Register(app)` the extension registers constructors for:

- `aisdk.LLMManager`
- `aisdk.StateStore`
- `aisdk.VectorStore`
- `*AgentFactory`
- `*AgentManager`

All are registered eagerly, so constructor problems surface during startup instead of at first request.

### 2. Smart Fallbacks for Stores

- State store:
  - tries existing DI service (`stateStore`)
  - else builds from config (`memory`, `postgres`, `redis`)
  - on failure falls back to in-memory store with `24h` TTL
- Vector store:
  - tries existing DI service (`vectorStore`)
  - else builds from config
  - on failure falls back to in-memory vector store

### 3. Agent Template System (8 Built-In Types)

Each template includes a system prompt and three tools.

| Type | Primary Scope |
|---|---|
| `cache_optimizer` | Cache hit/miss and eviction strategy |
| `scheduler` | Scheduling and resource allocation |
| `anomaly_detector` | Statistical anomaly analysis |
| `load_balancer` | Traffic and capacity balancing |
| `security_monitor` | Security anomaly and threat response |
| `resource_manager` | CPU, memory, and allocation optimization |
| `predictor` | Forecasting and trend prediction |
| `optimizer` | General system optimization |

### 4. REST Controller for Agent Management

`AgentController` exposes:

- CRUD for dynamic agents
- template listing
- execution/chat endpoints

Routes are explicit and only exist if you mount the controller.

## Optional Feature Sets in Subpackages

These are available in the module, but not automatically bootstrapped by `ai.Extension`:

- `inference`: high-throughput inference pipeline, batching, caching, scaling
- `training`: model trainer, dataset manager, pipeline manager
- `middleware`: intelligent rate limit, anomaly detection, personalization, response optimization, adaptive load balancing, security scanner
- `monitoring`: health monitor, metrics collector, alert manager, dashboard

## Important Implementation Limits (Current)

- `LLMConfiguration.Providers` is not auto-registered into `LLMManager`; provider registration is manual.
- `CreateVectorStore` only fully supports `memory` today.
  - `postgres`, `pinecone`, and `weaviate` return not-implemented errors.
  - extension-level constructor then falls back to memory vector store.
- Training DI services are registered based on `Training.Enabled`.
- `EnableTraining` in top-level config is not the registration switch by itself.
- Agent definitions are stored in-memory by `AgentManager`.

## Operational Guidance

- Use type-based injection for app services (`forge.InjectType[T]`) and only use key aliases for compatibility.
- Treat vector persistence as memory-only unless you deliberately replace the constructor with your own implementation.
- If you need durability for agent definitions (not only conversation state), persist your own metadata outside `AgentManager`.