LangGraph BaseStore adapter for Lithtrix agent memory
Project description
lithtrix-langgraph
A LangGraph BaseStore adapter that gives your graph persistent, per-agent memory backed by the Lithtrix API — identity, memory, and reputation infrastructure for AI agents.
What this is (and isn't)
This package is a memory store adapter only. It gives a LangGraph graph a store= that reads and writes to Lithtrix's memory API, so your agent's memory survives restarts and is queryable by key or by semantic search.
It does not include Lithtrix's swarm primitives (spawning sub-agents, signed delegation contracts, audit traces) — those exist in the wider Lithtrix API but are not wrapped by this package today. If you need them, call the REST API directly; see docs.lithtrix.ai.
Install
pip install lithtrix-langgraph
Requires Python 3.11+. If you're not in a virtual environment, installing into system Python can fail with a permission error — use a venv (python -m venv .venv && source .venv/bin/activate) or pip install --user lithtrix-langgraph instead.
1. Get an API key
Every Lithtrix agent needs its own identity and key. Register one with a single unauthenticated call — no dashboard, no approval step:
curl -X POST https://api.lithtrix.ai/v1/register \
-H "Content-Type: application/json" \
-H "User-Agent: my-agent/1.0" \
-d '{
"agent_name": "my-langgraph-agent",
"owner_identifier": "you@example.com",
"agree_to_terms": true
}'
agent_name + owner_identifier must be unique together — reusing the same pair returns 409. agree_to_terms must be true (accepts the Gentle-Agent Agreement).
The response is a full agent record (identity keys, tier info, etc.) — the only field you need right now is api_key (starts with ltx_). Save it now — it is only ever shown once. Set it as an environment variable:
export LITHTRIX_API_KEY=ltx_your_key_here
2. Configure the store
from lithtrix_langgraph import LithtrixStore
store = LithtrixStore() # reads LITHTRIX_API_KEY from the environment
api_key / api_url can also be passed as constructor kwargs, which override the environment — useful in tests or when running multiple agents from one process.
| Variable | Required | Default |
|---|---|---|
LITHTRIX_API_KEY |
Yes | — |
LITHTRIX_API_URL |
No | https://api.lithtrix.ai |
3. A complete working example
Compile a graph with store= and any node can read and write memory via LangGraph's get_store():
from lithtrix_langgraph import LithtrixStore
from langgraph.graph import StateGraph
from langgraph.config import get_store
from typing_extensions import TypedDict
class State(TypedDict):
note: str
def remember(state: State) -> State:
store = get_store()
# "my-agent" here is just a namespace prefix you choose for organizing keys —
# it has no relationship to the agent_name you registered with above.
store.put(("my-agent",), "last-note", {"text": state["note"]})
item = store.get(("my-agent",), "last-note")
return {"note": item.value["text"]}
store = LithtrixStore()
graph = StateGraph(State)
graph.add_node("remember", remember)
graph.set_entry_point("remember")
graph.set_finish_point("remember")
compiled = graph.compile(store=store)
result = compiled.invoke({"note": "hello from LangGraph"})
print(result) # {'note': 'hello from LangGraph'}
This example was run against the live production API as part of writing this README — not just tested against mocks.
Note: the namespace tuple (
("my-agent",)above) is just a prefix you choose for organizing keys — it has no relationship to theagent_nameyou registered with. YourLITHTRIX_API_KEYis what determines whose memory you're reading and writing; the namespace can be anything.
Key mapping
LangGraph's (namespace_tuple, key) gets flattened into a single Lithtrix key, since Lithtrix keys are flat strings (1–128 chars, charset [a-zA-Z0-9-_.:]):
| LangGraph call | Lithtrix key |
|---|---|
put(("user", "alice"), "preferences", ...) |
user:alice:preferences |
put((), "preferences", ...) |
preferences |
An empty namespace () passes the key through unchanged — useful if you're writing keys that need to match a flat naming convention from another system.
Values
- Put: LangGraph values are
dict→PUT /v1/memory/{key}with body{"value": <dict>}. Serialized size is checked locally at 512 KiB before HTTP (mirrors APIMEMORY_VALUE_TOO_LARGE/ HTTP 413). - Get: JSON objects are returned as-is. String/number/array payloads (DeerFlow Rung 1) are wrapped as
{"content": <raw>}. - Timestamps: Uses Lithtrix
created_at/updated_atwhen present; otherwisedatetime.now(UTC)on read. - TTL:
supports_ttl = False;PutOp.ttlis ignored.
SearchOp supported subset
| Feature | Support |
|---|---|
namespace_prefix |
Yes → Lithtrix list prefix |
query (semantic) |
Yes → GET /v1/memory/search |
limit / offset |
Yes (best-effort pagination) |
filter with query |
Partial — exact top-level match applied client-side after semantic search |
filter without query |
Partial — list keys under prefix, fetch values, exact match only |
$eq / $ne / $gt / … |
No — raises NotImplementedError |
| Cross-namespace search | No |
HTTP errors
401/403/413/422 responses propagate as LithtrixAPIError with error_code when the API returns structured JSON (e.g. MEMORY_VALUE_TOO_LARGE). 5xx responses are safe to retry — they indicate a transient server-side issue, not a problem with your request.
Free tier
New agents get 1,000 memory writes/month and 5 MiB of KV storage, no credit card required. Reads and semantic search don't count against the write limit. See docs.lithtrix.ai for paid tiers if you outgrow it.
Contributing
The source lives in Lithtrix's main repository, which is private — there's no public repo to file a pull request against. If you hit a bug or want a feature, email hello@lithtrix.ai.
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