redis-memory-backend

Redis backend for conversation state persistence and caching

509 stars

Best use case

redis-memory-backend is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Redis backend for conversation state persistence and caching

Teams using redis-memory-backend should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/redis-memory-backend/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/ai-agents-conversational/skills/redis-memory-backend/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/redis-memory-backend/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How redis-memory-backend Compares

Feature / Agent	redis-memory-backend	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Redis backend for conversation state persistence and caching

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Redis Memory Backend Skill

## Capabilities

- Configure Redis for conversation state storage
- Implement message history persistence
- Set up Redis caching for LLM responses
- Configure TTL-based memory expiration
- Implement Redis Pub/Sub for real-time updates
- Design efficient key schemas

## Target Processes

- conversational-memory-system
- chatbot-design-implementation

## Implementation Details

### Core Components

1. **Message Store**: RedisChatMessageHistory
2. **Cache**: LLM response caching
3. **State Store**: Conversation state persistence
4. **Pub/Sub**: Real-time updates

### Configuration Options

- Redis connection settings
- Key prefix configuration
- TTL settings
- Serialization format
- Cluster configuration

### Key Schema Patterns

- session:{session_id}:messages
- cache:llm:{prompt_hash}
- state:{user_id}:{key}

### Best Practices

- Use appropriate data structures
- Configure proper TTLs
- Implement connection pooling
- Monitor memory usage

### Dependencies

- redis
- langchain-community (RedisChatMessageHistory)

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