Update app.py

app.py

@@ -3,21 +3,25 @@ import requests
 import gradio as gr
 
 #
-# 1) Retrieve your Hugging Face token (with read access) for the private space
+# 1) Retrieve your Hugging Face token (with read or write access) for the private space
 #
 HF_TOKEN = os.getenv("HF_TOKEN", "").strip()
 HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"}
 
 #
-# 2) Private space endpoint:
-#    Must match the domain from your private Space's "Embed" or "View App."
+# 2) Private space endpoint
+#
+# Make sure this EXACT domain matches "Embed this Space" or "View App" from your private space.
+# If your private space is "jtdearmon-rag-dal-budget",
+# and the embed link is "https://jtdearmon-rag-dal-budget.hf.space",
+# then use that domain here:
 #
 PRIVATE_SPACE_ROOT = "https://jtdearmon-rag-dal-budget.hf.space"
 
 #
 # 3) Utility to call a specific Gradio function in the private space.
-#    - function_index=0 => /run/predict  (for run_query)
-#    - function_index=1 => /run/predict_1 (for handle_feedback)
+#    function_index=0 => /run/predict
+#    function_index=1 => /run/predict_1
 #
 def call_private_space(function_index, data_list):
     """
@@ -26,42 +30,38 @@ def call_private_space(function_index, data_list):
       - function_index=1 => /run/predict_1
     data_list => the "data": [...] array matching that function’s inputs
     """
-    # Base endpoint
     url = f"{PRIVATE_SPACE_ROOT}/run/predict"
-    # If we specify function_index>0, call /run/predict_1, etc.
     if function_index > 0:
         url += f"_{function_index}"
 
     payload = {"data": data_list}
     try:
-        # If you really want to skip SSL checks, add `verify=False`:
-        resp = requests.post(url, headers=HEADERS, json=payload,verify=False)
+        # If you see SSL errors, keep verify=False. 
+        # If you'd like to enable normal SSL checks, set verify=True or remove it:
+        resp = requests.post(url, headers=HEADERS, json=payload, verify=False)
         resp.raise_for_status()  # Raises HTTPError on 4xx/5xx
         json_resp = resp.json()
-        # Typically the function’s first return is json_resp["data"][0]
+        # Typically the function’s first return is in json_resp["data"][0]
         return json_resp["data"][0]
     except Exception as e:
         return f"Error calling private space: {e}"
 
 #
-# 4) The two main interactive functions from your private code:
-#    - run_query(user_query, use_summary)
-#    - handle_feedback(user_query, answer, feedback_option)
+# 4) The two main interactive functions that mirror your private code:
 #
 def run_query(user_query, use_summary):
-    # This calls /run/predict (function_index=0 in the private Space)
+    # This calls /run/predict (function_index=0)
     return call_private_space(0, [user_query, use_summary])
 
 def handle_feedback(user_query, answer, feedback_option):
-    # This calls /run/predict_1 (function_index=1 in the private Space)
+    # This calls /run/predict_1 (function_index=1)
     return call_private_space(1, [user_query, answer, feedback_option])
 
 #
-# 5) Build the UI layout to mirror your private space,
-#    now loading dal_logo.png locally from this public repo.
+# 5) Build a UI to demonstrate the calls
 #
 with gr.Blocks() as demo:
-    # Top row: logo on the left, title on the right
+    # Top row
     with gr.Row():
         with gr.Column(scale=1, min_width=100):
             gr.Image(
@@ -72,13 +72,11 @@ with gr.Blocks() as demo:
                 height=80
             )
         with gr.Column(scale=6):
-            gr.Markdown("## Dallas Budget RAG Model")
+            gr.Markdown("## Dallas Budget RAG Model - Public Space")
             gr.Markdown(
-                "Based on the Adopted Annual Operating and Capital Budget. "
-                "Only the last 5 queries are kept in the conversation."
+                "Calls the private Space for actual processing."
             )
 
-    # User query, hidden checkbox, and Get Answer button
     user_query = gr.Textbox(
         label="Your Query",
         lines=1,
@@ -94,7 +92,7 @@ with gr.Blocks() as demo:
     # Output area
     answer_output = gr.Markdown(label="AI Answer")
 
-    # Feedback section
+    # Feedback
     feedback_radio = gr.Radio(
         choices=["👍", "⚖️", "👎"],
         value="⚖️",
@@ -103,7 +101,7 @@ with gr.Blocks() as demo:
     feedback_btn = gr.Button("Submit Feedback")
     feedback_result = gr.Markdown()
 
-    # Wire the buttons to the private space endpoints
+    # Wire the buttons
     get_answer_btn.click(
         fn=run_query,
         inputs=[user_query, use_summary_chk],
@@ -119,15 +117,12 @@ with gr.Blocks() as demo:
     gr.HTML(
         """
         <div style="text-align: center; margin-top: 20px;">
-            Built with 
-            <a href="https://gradio.app" target="_blank">Gradio</a>
-            &nbsp;|&nbsp;
             Built by 
-            <a href="https://dearmonanalytics.com" target="_blank">Dearmon Analytics</a>
+            <a href="https://dearmonanalytics.com" target="_blank">Dearmon Analytics</a> | 
+            <a href="https://huggingface.co/spaces" target="_blank">HF Spaces</a>
         </div>
         """
     )
 
-# Launch the public interface
 if __name__ == "__main__":
     demo.launch()