citadeldb-crewai

CrewAI memory backed by Citadel. Encrypted at rest, embedded in your process, and deletes that destroy the record's key rather than its row.

pip install citadeldb-crewai

Route your crews' memory through Citadel in one call at startup:

from citadeldb_crewai import use_citadel

use_citadel("crew_memory.cdl", key="your-passphrase")

Crews then work unchanged:

crew = Crew(agents=[...], tasks=[...], memory=True)

A crew that names its own backend keeps it, so this will not displace a deliberate storage="qdrant-edge". Crews may also name Citadel outright once use_citadel has run: Memory(storage="citadel").

To route one crew instead of the whole process, hand the backend over directly and skip the startup call:

from crewai.memory.unified_memory import Memory
from citadeldb_crewai import CitadelBackend

backend = CitadelBackend("crew_memory.cdl", key="your-passphrase")
crew = Crew(agents=[...], tasks=[...], memory=Memory(storage=backend))

Or drive the backend directly

from citadeldb_crewai import CitadelBackend
from crewai.memory.storage.backend import MemoryRecord

backend = CitadelBackend("crew_memory.cdl", key="your-passphrase")

backend.save([
    MemoryRecord(
        content="the deploy failed because the disk was full",
        scope="/team/ops",
        categories=["incident"],
        metadata={"env": "prod"},
        importance=0.9,
    )
])

hits = backend.search(query_embedding, scope_prefix="/team", limit=5)
for record, score in hits:
    print(f"{score:.3f}  {record.content}")

Deletes destroy the key

Every record is sealed under its own key. Deleting destroys that key, so the bytes on disk stay unreadable instead of being marked deleted and living on in backups.

backend.delete(record_ids=["abc123"])                      # one record
backend.delete(scope_prefix="/team/ops", categories=["incident"])
backend.delete(scope_prefix="/team", older_than=cutoff)    # retention sweep
backend.reset("/users/alice")                              # a whole subtree

reset on a per-user scope is what a data-deletion request usually needs: the subtree becomes unreadable rather than merely unlisted.

Importance is a real ranking signal

MemoryRecord.importance maps onto Citadel's native atom score, so it survives as something recall ranks by rather than as metadata the store carries and ignores.

Notes

CrewAI embeds queries itself and hands the backend a vector, so search runs vector recall plus the scope, category, and metadata predicates the protocol defines.

Citadel is embedded and takes an exclusive lock on the file, so build one backend per database and share it. use_citadel does that for you.

Your crew's own embeddings are stored as-is, so recall runs in the same vector space the crew queries with, and no text is re-embedded. Set dim to your embedding model's width if it is not OpenAI's 1536-wide text-embedding-3-small:

use_citadel("crew_memory.cdl", key="pw", dim=768)

A record saved without an embedding still stores and still comes back through get_record, list_records, and every delete filter; it just does not rank in vector search.

License

Apache-2.0