Update app.py

app.py

@@ -2,11 +2,11 @@ import gradio as gr
 import requests
 import json
 import io
+import os
 from PIL import Image
 import base64
 from prance import ResolvingParser
 
-
 SCHEMA_URL = "http://localhost:5000/openapi.json"
 FILENAME = "openapi.json"
 schema_response = requests.get(SCHEMA_URL)
@@ -18,55 +18,83 @@ with open(FILENAME, "wb") as f:
     f.write(r.content)
 
 parser = ResolvingParser(FILENAME)
+api_spec = parser.specification
 print(parser.specification)
 
-
 def extract_property_info(prop):
-    # Handle 'allOf' by merging all contained properties (assuming simple case of enum merging)
-    if "allOf" in prop:
-        combined_prop = {}
-        for subprop in prop["allOf"]:
-            combined_prop.update(subprop)
-        prop = combined_prop
-    return 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 create_gradio_app(api_spec, api_url):
     inputs = []
-    input_schema = api_spec["components"]["schemas"]["PredictionRequest"]["properties"][
-        "input"
-    ]["properties"]
+    input_schema = api_spec["components"]["schemas"]["Input"]["properties"]
 
     for name, prop in input_schema.items():
+        #print(prop)
         prop = extract_property_info(
             prop
         )  # Extract property info correctly for 'allOf'
         print(prop)
         if "enum" in prop:
             input_field = gr.Dropdown(
-                choices=prop["enum"], label=name, value=prop.get("default")
+                choices=prop["enum"], label=prop.get("title"), info=prop.get("description"), value=prop.get("default")
             )
         elif prop["type"] == "integer":
-            input_field = gr.Number(
-                label=name,
+            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,
             )
         elif prop["type"] == "number":
-            input_field = gr.Number(
-                label=name,
+            input_field = gr.Slider(
+                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=name, 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=name)
+            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=name, value=prop.get("default"))
+            input_field = gr.Textbox(
+                label=prop.get("title"),
+                info=prop.get("description"),
+            )
         inputs.append(input_field)
 
     def predict(**kwargs):
@@ -102,9 +130,6 @@ def create_gradio_app(api_spec, api_url):
     return gr.Interface(fn=predict, inputs=inputs, outputs=output_component)
 
 
-# Use the modified function with the API URL
-api_spec = parser.specification
-
 API_URL = "http://localhost:5000/predictions"
 app = create_gradio_app(api_spec, API_URL)
 app.launch()