langgraph-agentram
An AgentRAM-backed BaseStore for LangGraph. It gives your LangGraph agents cross-thread long-term memory through a hosted key-value API, with no vector database and no embedding pipeline to run.
LangGraph's long-term memory is built on stores: JSON values organized by a namespace and a key. AgentRAM is a hosted memory API with exactly that shape, so this adapter is a thin, honest bridge between the two.
Install
pip install langgraph-agentram
Get a free AgentRAM API key at agentram.dev. New accounts start with 1,000 credits, no card required.
Use it
Pass the store to your agent and it gains memory that survives across threads:
from langchain.agents import create_agent
from langgraph_agentram import AgentRAMStore
store = AgentRAMStore(api_key="agentram_your_key_here")
agent = create_agent("claude-sonnet-4-6", tools=[], store=store)
Or use the store directly:
store.put(("memories", "user-1"), "language", {"value": "French"})
item = store.get(("memories", "user-1"), "language")
print(item.value) # {"value": "French"}
# list a namespace, or text-search within it
store.search(("memories", "user-1"))
store.search(("memories", "user-1"), query="French")
How it maps to AgentRAM
- A namespace tuple becomes an AgentRAM
agent_id, joined with/(for example("memories", "user-1")becomesmemories/user-1). - The key is the AgentRAM key.
- The value dict is JSON-encoded into AgentRAM's value field.
Honest limits
This adapter does what AgentRAM does, and nothing it does not.
searchis a text match, not semantic ranking.scoreis alwaysNone. That is the point: memory without a vector database.searchtreats the namespace you pass as a full namespace, not a prefix to walk into nested sub-namespaces.list_namespacesis not supported. AgentRAM has no endpoint to enumerate namespaces, so the adapter raises rather than return a wrong answer. Track namespaces in your own app if you need them.- A namespace maps to an
agent_idcapped at 100 characters, and a value is capped at 5,000 characters. Both raise a clear error if exceeded, rather than truncating. - Per-item TTL is not mapped in this version.
Config
api_key(required): your key, starts withagentram_.base_url(optional): defaults tohttps://api.agentram.dev.
Links
- AgentRAM: https://agentram.dev
- API docs: https://agentram.dev/docs.html
- Issues: https://github.com/seanmarkwei/langgraph-agentram/issues
MIT
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