wehub-resource-sync
75 lines
1.9 KiB
Python
75 lines
1.9 KiB
Python
import requests
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# __doc_import_begin__
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from ray import serve
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from ray.serve.handle import DeploymentHandle
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from ray.serve.gradio_integrations import GradioIngress
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import gradio as gr
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import asyncio
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from transformers import pipeline
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# __doc_import_end__
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# __doc_models_begin__
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@serve.deployment
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class TextGenerationModel:
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def __init__(self, model_name):
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self.generator = pipeline("text-generation", model=model_name)
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def __call__(self, text):
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generated_list = self.generator(
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text, do_sample=True, min_length=20, max_length=100
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)
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generated = generated_list[0]["generated_text"]
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return generated
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app1 = TextGenerationModel.bind("gpt2")
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app2 = TextGenerationModel.bind("distilgpt2")
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# __doc_models_end__
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# __doc_gradio_server_begin__
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@serve.deployment
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class MyGradioServer(GradioIngress):
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def __init__(
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self, downstream_model_1: DeploymentHandle, downstream_model_2: DeploymentHandle
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):
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self._d1 = downstream_model_1
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self._d2 = downstream_model_2
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super().__init__(
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lambda: gr.Interface(
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self.fanout, "textbox", "textbox", api_name="predict"
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)
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)
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async def fanout(self, text):
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[result1, result2] = await asyncio.gather(
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self._d1.remote(text), self._d2.remote(text)
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)
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return (
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f"[Generated text version 1]\n{result1}\n\n"
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f"[Generated text version 2]\n{result2}"
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)
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# __doc_gradio_server_end__
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# __doc_app_begin__
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app = MyGradioServer.bind(app1, app2)
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# __doc_app_end__
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# Test example code
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serve.run(app)
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response = requests.post(
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"http://127.0.0.1:8000/gradio_api/run/predict/", json={"data": ["My name is Lewis"]}
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)
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assert response.status_code == 200
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print(
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"gradio-integration-parallel.py: Response from example code is",
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response.json()["data"],
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)
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