api updates

app.py

@@ -98,19 +98,14 @@ def run_api(predictor):
     'API mode' for this Streamlit app. 
     Expects a query param ?api=1&image_url=<PUBLIC_IMAGE_URL>
 
-    Example usage (from command line):
-        curl -X GET "https://your-username-your-app.hf.space/?api=1&image_url=https://raw.githubusercontent.com/yourimage.jpg"
-
-    The response is HTML with an embedded JSON, but you can often parse it directly in Python:
-        >>> import requests
-        >>> response = requests.get("https://your-username-your-app.hf.space/?api=1&image_url=...")
-        >>> print(response.text)       # prints the entire HTML with JSON
-        # or sometimes:
-        >>> data = response.json()     # may work depending on how the client interprets the response
-        >>> print(data)
+    Example usage:
+        curl "https://YOUR-SPACE.hf.space/?api=1&image_url=<some_image_url>"
+    
+    WARNING: You will still get HTML with embedded JSON. That's a Streamlit limitation.
     """
-    params = st.experimental_get_query_params()  # or st.query_params in Streamlit 1.19+
-    image_url = params.get("image_url", [None])[0]
+    # Use st.query_params (not st.experimental_get_query_params)
+    params = st.query_params
+    image_url = params.get("image_url", [None])[0]  # `query_params` returns dict of lists
     
     if not image_url:
         st.json({"error": "No 'image_url' provided. Usage: ?api=1&image_url=<URL>"})
@@ -128,7 +123,7 @@ def run_api(predictor):
     
     image_bytes = response.content
     # Check file size (limit 10MB)
-    image_size_mb = len(image_bytes)/(1024*1024)
+    image_size_mb = len(image_bytes) / (1024 * 1024)
     if image_size_mb > 10:
         st.json({"error": f"Image size {image_size_mb:.2f}MB exceeds 10MB limit."})
         st.stop()
@@ -165,13 +160,14 @@ def run_api(predictor):
         else:
             prediction_label = "Vespidae (wasp/hornet)"
 
-    # Return results as JSON and stop further Streamlit processing
+    # Return results as JSON, but note that Streamlit wraps this in HTML
     st.json({
         "honeybee_score": honeybee_score,
         "bumblebee_score": bumblebee_score,
         "vespidae_score": vespidae_score,
         "prediction_label": prediction_label
     })
+    # Stop execution so the normal UI won't render
     st.stop()
 
 def run_ui(predictor):
@@ -231,7 +227,7 @@ def main():
     predictor = load_model()
 
     # Decide whether we are in 'API mode' or normal UI mode
-    query_params = st.experimental_get_query_params()
+    query_params = st.query_params  # Replaces st.experimental_get_query_params
     if "api" in query_params:
         run_api(predictor)
     else: