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Caura Rail for Python

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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])

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.

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