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claude-codedevelopment

Babysitter langchain-memory

LangChain memory integration including ConversationBufferMemory, ConversationSummaryMemory, and vector-based memory

install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/ai-agents-conversational/skills/langchain-memory" ~/.claude/skills/a5c-ai-babysitter-langchain-memory && rm -rf "$T"
manifest: library/specializations/ai-agents-conversational/skills/langchain-memory/SKILL.md
tags
#conversation-memory#langchain-integration#chatbot-memory#vector-memory#summary-memory
source content

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)