Cryptographically verified, relational, persistent memory for AI agents.
Project description
cryptomem
Cryptographically verified, relational, persistent memory for AI agents.
This package is the Python engine. Every fact is SHA-256 hashed and Ed25519 signed at write time; at read time each node is re-verified, and tampered or unsigned facts are dropped so the agent abstains rather than guessing.
Install
pip install cryptomem # core engine
pip install "cryptomem[serve,local]" # + Ollama-compatible sidecar & local embeddings
Published on PyPI; the typed Rust client is
cryptomem-rs on crates.io.
from cryptomem import MemoryClient
mem = MemoryClient()
mem.archive("Project Phoenix", "Budget approved at $4.2M for FY26.")
for hit in mem.query("What budget did Project Phoenix get?"):
print(hit.node.content, hit.confidence)
print(mem.answer("What budget did Project Phoenix get?"))
Runs on CPU-only hardware with zero model downloads via the default stub
embedder and in-memory SQLite store. See the repository docs/ for the full
architecture and roadmap.
Beyond retrieval
mem.respond(...)— answer plus a provenance block (injected node ids, verification status, Merkle root).mem.proof(node_id)— a verifiable Merkle inclusion proof against the current ledger root.mem.confidence(...)— semantic-entropy confidence over sampled answers.mem.verify_answer(draft)— Chain-of-Verification re-check of a draft.mem.contradictions()— same-entity nodes whose content diverges.mem.suggest(...),mem.triggers(),mem.stage_facts(...),mem.pending(),mem.confirm(node_id)— proactive planner, triggers, and write-back of staged (pending) facts that you later confirm.
Store backends
Selected via CRYPTOMEM_MODE (or Settings(mode=...)):
sqlite(default) — zero-config local store; Python-side vector search.neo4j— graph-native store over the Bolt driver (pip install "cryptomem[neo4j]",CRYPTOMEM_NEO4J_URI=...).remote— signs locally and POSTs verbatim to a/cmem/v1/*backend (CRYPTOMEM_BACKEND_URL=...); falls back to SQLite if the backend is down.
Use with agno
Expose verified memory as agno tools so the agent answers only from signed facts (or abstains):
from agno.agent import Agent
from agno.models.ollama import Ollama
from cryptomem import MemoryClient
MEM = MemoryClient()
def recall_verified_memory(query: str) -> str:
"""Return only signature-verified facts; abstain if none match."""
hits = [h for h in MEM.query(query, top_k=5) if h.verified]
if not hits:
return "NO_VERIFIED_MEMORY: abstain; do not guess."
return "\n".join(f"- [{h.node.node_id}] {h.node.content}" for h in hits)
agent = Agent(model=Ollama(id="qwen2.5:0.5b"), tools=[recall_verified_memory])
agent.print_response("What budget did Project Phoenix get?")
Full runnable example: examples/agno_verified_memory.py.
See also ../docs/framework_integrations.md.
Optional extras
pip install "cryptomem[local]" (MiniLM embeddings), [serve] (FastAPI
Ollama-compatible sidecar + CLI), [neo4j] (graph store), [agno] (agno
integration example), [dev] (tooling).
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