Caura Rail for Python
Memory operations around agent turns: fetch governance rules and relevant facts from Caura before your agent runs, then extract and store facts from the completed turn. Fully typed, synchronous and asynchronous.
python -m pip install caura-rail
from caura_rail import MemoryScope, Rail, RestMemoryStore
with RestMemoryStore.from_env() as store: # CAURA_URL, CAURA_API_KEY
rail = Rail(store, MemoryScope(agent_id="support-1"))
with rail.turn("Remember: We deploy in eu-west-1.") as turn:
turn.reply = "Noted. " + turn.context.text # pass context to your model
print(turn.reply, [w.status for w in turn.writes])
Prefer the thin caura-client package when you only need to call the API; Rail
adds the turn lifecycle, governance ordering, extraction, and replay on top.
Full documentation, including the guide, API reference, and reliability
semantics, lives in the
repository.
A TypeScript package with the same semantics is published as @caura/rail.
Licensed under Apache-2.0.
1 maintainer
Metadata
1 maintainer
Release files for caura-rail 1.0.0
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