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Typed Python client for the Audrey LLM memory server

Project description

Audrey Python SDK

Typed Python client for the Audrey REST API.

Install

pip install audrey-memory

For local development from this repository:

cd python
python -m pip install -e .

Quick Start

Start Audrey's REST API:

npm install -g audrey --allow-scripts=better-sqlite3,onnxruntime-node,sharp,protobufjs
audrey serve

Then use the client:

from audrey_memory import Audrey

brain = Audrey(
    base_url="http://127.0.0.1:7437",
    api_key="secret",
    agent="support-agent",
)

memory_id = brain.encode(
    "Stripe returns HTTP 429 above 100 req/s",
    source="direct-observation",
    tags=["stripe", "rate-limit"],
)

results = brain.recall("stripe rate limits", limit=5)
snapshot = brain.snapshot()
brain.close()

Restore snapshots only into an empty Audrey store, such as a sidecar started with a fresh AUDREY_DATA_DIR:

restore_target = Audrey(base_url="http://127.0.0.1:7437", api_key="secret")
restore_target.restore(snapshot)
restore_target.close()

Async usage:

import asyncio

from audrey_memory import AsyncAudrey


async def main() -> None:
    async with AsyncAudrey(base_url="http://127.0.0.1:7437") as brain:
        await brain.health()
        await brain.encode("Deploy failed due to OOM", source="direct-observation")
        await brain.recall("deploy failure", limit=3)


asyncio.run(main())

Features

  • Sync and async clients powered by httpx
  • Pydantic request and response models
  • Bearer auth via AUDREY_API_KEY
  • Optional X-Audrey-Agent header on client requests
  • Snapshot export and restore support

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