| import gradio | |
| def my_inference_function(name): | |
| return "Hello " + name + "!" | |
| gradio_interface = gradio.Interface( | |
| fn=my_inference_function, | |
| inputs="text", | |
| outputs="text", | |
| examples=[ | |
| ["Jill"], | |
| ["Sam"] | |
| ], | |
| title="REST API with Gradio and Huggingface Spaces", | |
| description="This is a demo of how to build an AI powered REST API with Gradio and Huggingface Spaces – for free! Based on [this article](https://www.tomsoderlund.com/ai/building-ai-powered-rest-api). See the **Use via API** link at the bottom of this page.", | |
| article="Test 2023" | |
| ) | |
| gradio_interface.launch() | |
| # import gradio as gr | |
| # import inspect | |
| # from gradio import routes | |
| # from typing import List, Type | |
| # # Monkey patch | |
| # def get_types(cls_set: List[Type], component: str): | |
| # docset = [] | |
| # types = [] | |
| # if component == "input": | |
| # for cls in cls_set: | |
| # doc = inspect.getdoc(cls) | |
| # doc_lines = doc.split("\n") | |
| # docset.append(doc_lines[1].split(":")[-1]) | |
| # types.append(doc_lines[1].split(")")[0].split("(")[-1]) | |
| # else: | |
| # for cls in cls_set: | |
| # doc = inspect.getdoc(cls) | |
| # doc_lines = doc.split("\n") | |
| # docset.append(doc_lines[-1].split(":")[-1]) | |
| # types.append(doc_lines[-1].split(")")[0].split("(")[-1]) | |
| # return docset, types | |
| # routes.get_types = get_types | |
| # # App code | |
| # def hallo(x): | |
| # return f"Hallo, {x}" | |
| # def hadet(x): | |
| # return f"Hadet, {x}" | |
| # with gr.Blocks() as blk: | |
| # # gr.Markdown("# Gradio Blocks (3.0) with REST API") | |
| # t = gr.Textbox() | |
| # b = gr.Button("Hallo") | |
| # a = gr.Button("Hadet") | |
| # o = gr.Textbox() | |
| # b.click(hallo, inputs=[t], outputs=[o]) | |
| # a.click(hadet, inputs=[t], outputs=[o]) | |
| # # gr.Markdown(""" | |
| # # ## API | |
| # # Can select which function to use by passing in `fn_index`: | |
| # # ```python | |
| # # import requests | |
| # # requests.post( | |
| # # url="https://hf.space/embed/versae/gradio-blocks-rest-api/+/api/predict/", json={"data": ["Jessie"], "fn_index": 0} | |
| # # ).json() | |
| # # requests.post( | |
| # # url="https://hf.space/embed/versae/gradio-blocks-rest-api/+/api/predict/", json={"data": ["Jessie"], "fn_index": 1} | |
| # # ).json() | |
| # # ``` | |
| # # Or using cURL | |
| # # ``` | |
| # # $ curl -X POST https://hf.space/embed/versae/gradio-blocks-rest-api/+/api/predict/ -H 'Content-Type: application/json' -d '{"data": ["Jessie"], "fn_index": 0}' | |
| # # $ curl -X POST https://hf.space/embed/versae/gradio-blocks-rest-api/+/api/predict/ -H 'Content-Type: application/json' -d '{"data": ["Jessie"], "fn_index": 1}' | |
| # # ```""") | |
| # ifa = gr.Interface(lambda: None, inputs=[t], outputs=[o]) | |
| # blk.input_components = ifa.input_components | |
| # blk.output_components = ifa.output_components | |
| # blk.examples = None | |
| # blk.predict_durations = [] | |
| # bapp = blk.launch() | |