Update app.py

app.py

@@ -22,96 +22,80 @@ api_spec = parser.specification
 print(parser.specification)
 
 def extract_property_info(prop):
-    # Initialize a dictionary to hold the combined properties
     combined_prop = {}
-    
-    # Identify the keywords to process. Extend this list if needed.
     merge_keywords = ["allOf", "anyOf", "oneOf"]
     
-    # Loop through each keyword to check if it exists in the prop
     for keyword in merge_keywords:
         if keyword in prop:
             for subprop in prop[keyword]:
                 combined_prop.update(subprop)
-            # After merging, remove the keyword to avoid confusion
             del prop[keyword]
     
-    # If no merge_keywords were found, copy the original property
     if not combined_prop:
         combined_prop = prop.copy()
     
-    # Preserve specific properties defined outside of merge_keywords,
-    # like 'description' and 'default', by updating them in combined_prop
     for key in ['description', 'default']:
         if key in prop:
             combined_prop[key] = prop[key]
     
-    # This returns the combined property with preserved 'description' and 'default' values.
     return combined_prop
 
+def sort_properties_by_order(properties):
+    ordered_properties = sorted(properties.items(), key=lambda x: x[1].get('x-order', float('inf')))
+    return ordered_properties
+
 def create_gradio_app(api_spec, api_url):
     inputs = []
+    outputs = []
     input_schema = api_spec["components"]["schemas"]["Input"]["properties"]
+    output_schema = api_spec["components"]["schemas"]["Output"]
+    ordered_input_schema = sort_properties_by_order(input_schema)
+    names = []
+    for name, prop in ordered_input_schema:
 
-    for name, prop in input_schema.items():
-        #print(prop)
-        prop = extract_property_info(
-            prop
-        )  # Extract property info correctly for 'allOf'
-        print(prop)
+        prop = extract_property_info(prop)
         if "enum" in prop:
             input_field = gr.Dropdown(
                 choices=prop["enum"], label=prop.get("title"), info=prop.get("description"), value=prop.get("default")
             )
         elif prop["type"] == "integer":
             input_field = gr.Slider(
-                label=prop.get("title"),
-                info=prop.get("description"),
-                value=prop.get("default"),
-                minimum=prop.get("minimum"),
-                maximum=prop.get("maximum"),
-                step=1,
+                label=prop.get("title"), info=prop.get("description"), value=prop.get("default"),
+                minimum=prop.get("minimum"), maximum=prop.get("maximum"), step=1,
             )
         elif prop["type"] == "number":
             input_field = gr.Slider(
-                label=prop.get("title"),
-                info=prop.get("description"),
-                value=prop.get("default"),
-                minimum=prop.get("minimum"),
-                maximum=prop.get("maximum"),
+                label=prop.get("title"), info=prop.get("description"), value=prop.get("default"),
+                minimum=prop.get("minimum"), maximum=prop.get("maximum"),
             )
         elif prop["type"] == "boolean":
-            input_field = gr.Checkbox(
-                label=prop.get("title"),
-                info=prop.get("description"),
-                value=prop.get("default")
-            )
+            input_field = gr.Checkbox(label=prop.get("title"), info=prop.get("description"), value=prop.get("default"))
         elif prop["type"] == "string" and prop.get("format") == "uri":
-            input_field = gr.File(
-                label=prop.get("title"),
-            )
-        else:  # Assuming string type for simplicity, can add more types as needed
-            input_field = gr.Textbox(
-                label=prop.get("title"),
-                info=prop.get("description"),
-            )
+            input_field = gr.File(label=prop.get("title"))
+        else:
+            input_field = gr.Textbox(label=prop.get("title"), info=prop.get("description"))
         inputs.append(input_field)
-
-    def predict(**kwargs):
+        names.append(name)
+    print(names)
+    data_field = gr.State(value=names)
+    inputs.append(data_field)
+    if output_schema["type"] == "string":
+        output_component = gr.Gallery(label="Output Image")
+        outputs.append(output_component)
+        outputs.append(data_field)
+    #else if there's multiple outputs
+    
+    def predict(*args):
+        print(args)
+        keys = args[-1]
         payload = {"input": {}}
-        for key, value in kwargs.items():
-            if isinstance(
-                value, io.BytesIO
-            ):  # For image inputs, convert to the desired format
-                value.seek(0)
-                value = (
-                    "data:image/jpeg;base64," + base64.b64encode(value.read()).decode()
-                )
+        for i, key in enumerate(keys):
+            value = args[i]
+            if(os.path.exists(value)):
+                value = "http://localhost:7860/file=" + value
             payload["input"][key] = value
-
-        response = requests.post(
-            api_url, headers={"Content-Type": "application/json"}, json=payload
-        )
+        print(payload)
+        response = requests.post(api_url, headers={"Content-Type": "application/json"}, json=payload)
         json_response = response.json()
 
         if "status" in json_response and json_response["status"] == "failed":
@@ -126,10 +110,9 @@ def create_gradio_app(api_spec, api_url):
 
         return output_images
 
-    output_component = gr.Gallery(label="Output Images")
-    return gr.Interface(fn=predict, inputs=inputs, outputs=output_component)
+    return gr.Interface(fn=predict, inputs=inputs, outputs=outputs if outputs else "label")
 
 
 API_URL = "http://localhost:5000/predictions"
 app = create_gradio_app(api_spec, API_URL)
-app.launch()
+app.launch(share=True)