langchain-superlocalmemory 0.1.0

LangChain chat message history backed by SuperLocalMemory V2 — 100% local, zero cloud

langchain-superlocalmemory

LangChain chat message history backed by SuperLocalMemory V2 -- 100% local, zero cloud.

Every message stays on your machine in a SQLite database. No API keys, no subscriptions, no telemetry.

Prerequisites

• Python 3.10+
• SuperLocalMemory V2 installed (~/.claude-memory/ must exist)
• langchain-core >= 1.0.0

Installation

pip install langchain-superlocalmemory

Or install from source:

cd integrations/langchain
pip install -e .

Quick Start

from langchain_core.messages import AIMessage, HumanMessage
from langchain_superlocalmemory import SuperLocalMemoryChatMessageHistory

# Create a history for a conversation session
history = SuperLocalMemoryChatMessageHistory(session_id="my-chat-session")

# Add messages
history.add_messages([
    HumanMessage(content="What is SuperLocalMemory?"),
    AIMessage(content="It's a local-first memory system for AI assistants."),
])

# Retrieve messages (chronological order)
for msg in history.messages:
    print(f"{msg.type}: {msg.content}")

# Clear the session
history.clear()

Features

• Local-first storage -- all data stays in ~/.claude-memory/memory.db
• Session isolation -- each session_id is completely independent
• Full LangChain compatibility -- implements BaseChatMessageHistory
• Persistent across restarts -- SQLite-backed, survives process exit
• Works alongside SLM -- messages are queryable via CLI, MCP, Skills, and REST API
• All message types -- HumanMessage, AIMessage, SystemMessage, FunctionMessage, ToolMessage
• additional_kwargs preserved -- metadata round-trips through serialization

Multi-Session Example

from langchain_superlocalmemory import SuperLocalMemoryChatMessageHistory

# Two independent conversations
support = SuperLocalMemoryChatMessageHistory(session_id="support-ticket-42")
coding = SuperLocalMemoryChatMessageHistory(session_id="code-review-pr-99")

# Messages are isolated -- support session cannot see coding session
support.add_messages([HumanMessage(content="My app is crashing")])
coding.add_messages([HumanMessage(content="Review this PR please")])

assert len(support.messages) == 1
assert len(coding.messages) == 1

Custom Database Path

By default the package uses ~/.claude-memory/memory.db. You can point to a different database:

history = SuperLocalMemoryChatMessageHistory(
    session_id="my-session",
    db_path="/path/to/custom/memory.db",
)

How It Works

Each LangChain message is stored as an individual memory entry in SuperLocalMemory V2:

• Content: JSON-serialized message (type, content, additional_kwargs)
• Tags: ["langchain", "langchain:session:<session_id>"]
• Importance: 3 (lower than user memories, so chat history does not crowd search results)
• Project: "langchain"

This means your LangChain conversations are visible in the SLM dashboard, searchable via slm recall, and accessible from any SLM-integrated tool.

License

MIT -- see LICENSE for details.

Links

• SuperLocalMemory V2 Repository
• Documentation
• LangChain Documentation