test as an API

app.py

@@ -1,19 +1,88 @@
-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()
+
+# 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()