Skip to main content

Mimir persistent memory backend for LangGraph agents

This project has been archived.

The maintainers of this project have marked this project as archived. No new releases are expected.

Project description

Mimir LangGraph Integration

Drop-in persistent long-term memory for LangGraph agents via Mimir.

Install

Install from source (not yet published to PyPI):

pip install langgraph
pip install -e integrations/langgraph/

Quick Start

from mimir_langgraph import MimirStore

# Create a Mimir-backed store
store = MimirStore(
    binary="mimir",  # or /usr/local/bin/mimir
    db_path="~/.mimir/data/mimir.db",
)

# Use as a drop-in BaseStore replacement
store.put(("users", "123"), "preferences", {"theme": "dark", "language": "en"})

item = store.get(("users", "123"), "preferences")
print(item.value)  # {"theme": "dark", "language": "en"}

# Search across namespaces
results = store.search(("users",), query="preferences theme")
for r in results:
    print(r.key, r.value, r.score)

Integration with LangGraph Agents

from langgraph.graph import StateGraph
from langgraph.store.base import BaseStore
from mimir_langgraph import MimirStore

# Use MimirStore as your long-term memory
store = MimirStore()

# Build your graph with store
graph = (
    StateGraph(AgentState)
    .add_node("agent", agent_node)
    .compile(store=store)
)

The store persists across sessions. Agents can retrieve context from previous interactions using store.search().

Configuration

Parameter Default Description
binary "mimir" Path to the mimir binary
db_path "~/.mimir/data/mimir.db" Path to the SQLite database
timeout 30.0 Tool call timeout in seconds
encryption_key None Path to AES-256-GCM key file
ollama_url None Ollama endpoint for hybrid search
embedding_model None Embedding model name (requires ollama_url)

How It Works

LangGraph's BaseStore interface maps cleanly onto Mimir's entity model:

LangGraph Mimir
namespace: tuple[str, ...] category: str (joined with /)
key: str key: str
value: dict body_json: str (JSON)
search() mimir_recall (FTS5)
put() mimir_remember
delete() mimir_forget

Requirements

  • Mimir v1.0.0+ installed (curl -sSL https://raw.githubusercontent.com/Perseus-Computing-LLC/mimir/main/scripts/bootstrap.sh | bash)
  • LangGraph >= 0.2.0
  • Python 3.10+

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mimir_langgraph-0.1.1.tar.gz (8.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mimir_langgraph-0.1.1-py3-none-any.whl (6.9 kB view details)

Uploaded Python 3

File details

Details for the file mimir_langgraph-0.1.1.tar.gz.

File metadata

  • Download URL: mimir_langgraph-0.1.1.tar.gz
  • Upload date:
  • Size: 8.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.13

File hashes

Hashes for mimir_langgraph-0.1.1.tar.gz
Algorithm Hash digest
SHA256 e7391204e0091dded9b3bccdc665a92297911b684c43ee8e1076b853565de3a5
MD5 27c98eae65f620dbf9d720bf0b5fec8f
BLAKE2b-256 9475de961244af08cce561e789ec64989d6c758ac9eb09436973baac2f5c6832

See more details on using hashes here.

File details

Details for the file mimir_langgraph-0.1.1-py3-none-any.whl.

File metadata

File hashes

Hashes for mimir_langgraph-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 bd003968315c83764780b9cfcb62011883b83bb2d5c7ef22c5e7eab7690e8e5c
MD5 609d440e6aa90440663f7e18eb85e5e3
BLAKE2b-256 337cfe87a8053ae18086d724f0b276b8e2de85f65204c3a15e042b28ed2bdd91

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page