LangGraph Integration

AegisLangGraphMemory gives a LangGraph graph long-term, semantic memory backed by Aegis Memory. It provides the two primitives every stateful graph needs:

retrieve relevant memories into state before a node reasons, and
remember what a node produced after it runs.

Because LangGraph state is just a dict / TypedDict, the adapter operates on plain state dicts and imports no langgraph package — it works with any graph shape and adds no hard dependency.

This is a memory helper, not a checkpointer. AegisLangGraphMemory does not implement LangGraph’s BaseCheckpointSaver and does not save or restore graph execution state / thread history. Use LangGraph’s own checkpointer for execution persistence; use this adapter for durable, security-scanned semantic memory.

Installation

pip install "aegis-memory[langgraph]"

The adapter itself needs no LangGraph install; the extra is provided for convenience when you also want LangGraph in the same environment.

Basic Usage

from aegis_memory import AegisClient
from aegis_memory.integrations.langgraph import AegisLangGraphMemory

memory = AegisLangGraphMemory(
    client=AegisClient(api_key="your-aegis-key", base_url="http://localhost:8000"),
    namespace="support-graph",
)

def agent_node(state: dict) -> dict:
    # 1. Retrieve relevant memory into state before reasoning.
    state = memory.load_into_state(state, state["question"], agent_id="assistant")
    context = state["aegis_memories"]  # list[dict]: content, metadata, score, agent_id

    # 2. ... call your model using `context` ...
    state["answer"] = run_model(state["question"], context)

    # 3. Persist what the node produced.
    memory.remember(state["answer"], agent_id="assistant",
                    metadata={"question": state["question"]})
    return state

API

retrieve(query, ...)

Returns a list of memory dicts relevant to query. Pass agent_id for cross-agent, scope-aware access control.

remember(content, ...)

Stores new memory. Content is security-scanned, embedded and (optionally) integrity-hashed by the server. Returns the memory ID.

load_into_state(state, query, ...)

Retrieves and writes results into state[key] (default aegis_memories), returning the mutated state — ideal as a node’s first line.

persist_from_state(state, content_key, ...)

Persists a value already in state (e.g. a node’s output). No-ops when the key is missing or empty.

Async graphs

For async LangGraph nodes, use AsyncAegisClient directly — it keeps API parity for add/query/vote/session/feature workflows while staying event-loop friendly:

from aegis_memory import AsyncAegisClient

async def graph_node(state):
    async with AsyncAegisClient(api_key="your-aegis-key") as client:
        memories = await client.query("plan context", agent_id="planner")
        return {"memories": [m.content for m in memories]}

Runnable example

A complete, server-free example (local mode, no API key) lives at examples/langgraph_basic.py.

LangGraph

LangGraph Integration

Installation

Basic Usage

API

retrieve(query, ...)

remember(content, ...)

load_into_state(state, query, ...)

persist_from_state(state, content_key, ...)

Async graphs

Runnable example

Next Steps

ACE Patterns

Security

​LangGraph Integration

​Installation

​Basic Usage

​API

retrieve(query, ...)

remember(content, ...)

load_into_state(state, query, ...)

persist_from_state(state, content_key, ...)

​Async graphs

​Runnable example

​Next Steps

ACE Patterns

Security

LangGraph Integration

Installation

Basic Usage

API

Async graphs

Runnable example

Next Steps