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()