Create app.py

app.py

@@ -0,0 +1,48 @@
+import os
+import requests
+import gradio as gr
+
+# 1. Retrieve the token from the environment
+HF_TOKEN = os.environ.get("HF_TOKEN")
+
+# 2. Function that calls the private Space
+def call_private_space(user_input):
+    """
+    Sends a POST request to the private Space's Gradio endpoint.
+    Adjust the URL or payload if your private Space uses something different.
+    """
+    # The private Space's URL - note 'jtdearmon--rag_dal_budget' matches the subdomain pattern
+    private_url = "https://jtdearmon--rag_dal_budget.hf.space/run/predict"
+    
+    headers = {
+        "Authorization": f"Bearer {HF_TOKEN}"
+    }
+    
+    # Typical Gradio JSON payload for a single text input
+    payload = {
+        "data": [user_input]
+    }
+    
+    # Send request
+    response = requests.post(private_url, headers=headers, json=payload)
+    response_data = response.json()
+    
+    # This depends on how your Gradio app in the private space returns output
+    # Usually it might be response_data["data"][0] if it returns one text output
+    result = response_data["data"][0]
+    
+    return result
+
+
+# 3. Create a Gradio interface
+interface = gr.Interface(
+    fn=call_private_space,
+    inputs="text",
+    outputs="text",
+    title="Public Demo for rag_dal_budget (Private)",
+    description="This public Space calls the private `rag_dal_budget` behind the scenes."
+)
+
+# 4. Launch the interface
+if __name__ == "__main__":
+    interface.launch()