/langchain-memory

name: langchain-memory
description: LangChain memory integration including ConversationBufferMemory, ConversationSummaryMemory, and vector-based memory
allowed-tools:
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graph:
  domains: [domain:software-engineering]
  specializations: [specialization:ai-agents-conversational]
  skillAreas: [skill-area:context-management, skill-area:retrieval-augmented-generation]
  roles: [role:ml-engineer, role:backend-engineer]
  workflows: [workflow:feature-development, workflow:ml-model-lifecycle]

LangChain Memory Skill

Capabilities

• Implement various LangChain memory types
• Configure ConversationBufferMemory for short-term recall
• Set up ConversationSummaryMemory for long conversations
• Integrate vector-based memory for semantic search
• Design memory retrieval strategies
• Handle memory persistence and serialization

Target Processes

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

Implementation Details

Memory Types

1. **ConversationBufferMemory**: Stores full conversation history 2. **ConversationBufferWindowMemory**: Rolling window of recent messages 3. **ConversationSummaryMemory**: Summarizes older messages 4. **ConversationSummaryBufferMemory**: Hybrid approach 5. **VectorStoreRetrieverMemory**: Semantic similarity-based retrieval

Configuration Options

• Memory key naming conventions
• Return message format (string vs messages)
• Summary LLM selection
• Vector store backend selection
• Token limits and window sizes

Dependencies

• langchain
• langchain-community
• Vector store client (optional)