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reference-ai/lib

The easiest way in python to run, deploy, and share AI models

1. Implement an PipelineAIProvider, or use one already provided

from referenceai.dataset.images.MNIST import MNISTPipelineAIProvider
provider = MNISTPipelineAIProvider()

2. Create a new PipelineAI

from referenceai.pipeline import PipelineAI
p = PipelineAI("my_provider", provider)

3. You can now train, classify, and update your model effortlessly

p.train()
p.classify(image)
p.update(new_image)
p.update_bulk([new_image_1, new_image_2])

4. Serve your model over RESTful or GraphQL interfaces

from referenceai.servers import GraphQLServer, RESTServer
g_server = GraphQLServer(p)
r_server = RESTServer(p)

g_server.run(port = 8080)
r_server.run(posrt = 3000)

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A python library to easily run, deploy, and share AI models

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