LangGraph Dev Setup

Use uv for deterministic Python environments and lockfile-driven installs. Use Docker for dependency services (memory-service, Keycloak, databases), not as your day-to-day Python package workflow.

Install the Package

pip install memory-service-langchain

Or with uv:

uv add memory-service-langchain

This single package includes both LangChain helpers (checkpointing, history middleware, FastAPI integration) and the LangGraph BaseStore implementation for episodic memories (memory_service_langchain.langgraph).

Baseline Runtime

3.11

[project]
name = "langgraph-doc-checkpoint-02-with-checkpointing"
version = "0.1.0"
description = "Memory Service LangGraph docs checkpoint app"
requires-python = ">=3.10"
dependencies = [
  "fastapi>=0.115.0,<1.0.0",
  "langgraph>=1.0.0,<2.0.0",
  "langchain-openai>=1.0.0,<2.0.0",
  "memory-service-langchain",
  "httpx>=0.28.0,<1.0.0",
  "uvicorn>=0.34.0,<1.0.0",
]

[tool.uv]
package = false

This is the minimum dependency set users need to run Memory Service-backed LangGraph examples.

Local Workflow

# one-time Python install
uv python install 3.11

# install deps from lock
cd python/examples/langgraph/doc-checkpoints/02-with-checkpointing
uv sync --frozen

# run app
uv run uvicorn app:app --host 0.0.0.0 --port 9090