Cache - Allocated Requirements¶

This document outlines the requirements allocated to the Cache component within the AgentHeaven architecture.

1. Overview¶

The Cache component is responsible for monitoring and temporarily storing function calls, LLM interactions, and agent trajectories.


2. Allocated Requirements¶

2.1 Functional Requirements¶

ID

Requirement

Implementation Details

Priority

FR-07

Cache/Memory

Implements monitoring and storage of system I/O

High

FR-08

Retrieval Engine

Provides cached data for retrieval methods

High

FR-27

Cache Backend Types

Implements Disk, Json, In-Memory, Callback, and Database cache backends

High

FR-28

Cache Entry Structure

Provides universal CacheEntry with func, inputs, output, and metadata

High

FR-29

Cache Decorators

Supports memoize and batch_memoize decorators for functions

High

FR-30

Async Support

Handles both synchronous and asynchronous function caching

High

FR-31

Streaming Support

Caches streaming generator functions (sync and async)

High

FR-32

Cache Annotation

Allows adding expected outputs and metadata to cache entries

Medium

FR-33

Cache Exclusion

Supports excluding specific parameters from cache key generation

Medium

FR-34

Cache Batch Operations

Provides efficient batch caching for multiple function calls

Medium

2.2 Non-Functional Requirements¶

ID

Requirement

Implementation Details

Priority

NFR-01

Performance

Implements caching for low-latency access

High

NFR-02

Observability

Records all LLM interactions and agent actions

Medium

NFR-10

Cache Hit Rate

Optimizes cache key generation for high hit rates

High

NFR-11

Memory Management

Implements efficient memory usage for cache entries

High

NFR-12

Thread Safety

Ensures cache operations are thread-safe

High

NFR-13

Cache Persistence

Provides reliable persistence for disk and database caches

Medium


2.3 Cross-Component Dependencies¶

Component

Description

KLStore

For persisting cached data as UKF records

Agent

For monitoring agent trajectories

LLM

For capturing LLM inputs/outputs


3. Implementation Notes¶

[Add implementation notes here]


4. Open Issues¶

[List any open issues or questions]


Further Exploration¶

Tip: For more information about the cache system in AgentHeaven, see:

Tip: For more information about AgentHeaven architecture, see: