🍱 BentoML v1.0.18 brings a new way of creating the server and client natively from Python.
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Start an HTTP or gRPC server and client asynchronously with a context manager.
server = HTTPServer("iris_classifier:latest", production=True, port=3000) # Start the server in a separate process and connect to it using a client with server.start() as client: res = client.classify(np.array([[4.9, 3.0, 1.4, 0.2]]))
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Start an HTTP or gRPC server synchronously.
server = HTTPServer("iris_classifier:latest", production=True, port=3000) server.start(blocking=True)
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As always, a client can be created and connected to an running server.
client = Client.from_url("http://localhost:3000") res = client.classify(np.array([[4.9, 3.0, 1.4, 0.2]]))
What's Changed
- chore(deps): bump coverage[toml] from 7.2.2 to 7.2.3 by @dependabot in #3746
- bugs: Fix an f-string bug in Tranformers framework. by @ssheng in #3753
- chore(deps): bump pytest from 7.2.2 to 7.3.0 by @dependabot in #3751
- chore(deps): bump bufbuild/buf-setup-action from 1.16.0 to 1.17.0 by @dependabot in #3750
- fix: BufferError when pushing model to BentoCloud by @aarnphm in #3737
- chore: remove codecov dependencies by @aarnphm in #3754
- feat: implement new serve API by @sauyon in #3696
- examples: Add a client example to quickstart by @ssheng in #3752
Full Changelog: v1.0.17...v1.0.18