Creating app.py

app.py

@@ -1,65 +1,11 @@
-import gradio as gr
-import inspect
-from gradio import routes
-from typing import List, Type
+import gradio
 
-# 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
+def my_inference_function(name):
+  return "Hello " + name + "!"
 
-# 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()
+gradio_interface = gradio.Interface(
+  fn = my_inference_function,
+  inputs = "text",
+  outputs = "text"
+)
+gradio_interface.launch()