langchain-memory

# 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)