redis-memory-backend

name	redis-memory-backend
description	Redis backend for conversation state persistence and caching
allowed-tools	["Read","Write","Edit","Bash","Glob","Grep"]
graph	{"domains":["domain:software-engineering"],"specializations":["specialization:ai-agents-conversational"],"skillAreas":["skill-area:context-management","skill-area:caching-strategies"],"roles":["role:ml-engineer","role:backend-engineer"],"workflows":["workflow:feature-development","workflow:ml-model-lifecycle"]}

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)