Update app.py

app.py

@@ -1,12 +1,44 @@
-import os
 import gradio as gr
+from gradio_client import Client
 
-# Access the Hugging Face token from environment variables
-hf_token = os.getenv("HF_TOKEN")
+# Initialize the Client for the Hugging Face Space
+client = Client("segestic/token-cost-calculator")
 
-# Load a private Hugging Face Space using the updated `token` parameter and `src='spaces'`
-app = gr.load(name="segestic/token-cost-calculator", src="spaces", token=hf_token)
+# Function to interact with the Hugging Face Space API
+def interact_with_space(system_prompt, user_prompt, assistant_response, model="gpt-4o"):
+    # Call the API with the provided inputs
+    result = client.predict(
+        system_prompt=system_prompt,
+        user_prompt=user_prompt,
+        assistant_response=assistant_response,
+        model=model,
+        api_name="/predict"
+    )
+    return result
 
-# Use the app
-output = app(["Input text"])
-print(output)
+# Define the Gradio interface for the UI
+def create_ui():
+    # Create the input and output components for the UI
+    with gr.Blocks() as demo:
+        # Inputs
+        system_prompt_input = gr.Textbox(label="System Prompt", placeholder="Enter system prompt here", lines=2)
+        user_prompt_input = gr.Textbox(label="User Prompt", placeholder="Enter user prompt here", lines=2)
+        assistant_response_input = gr.Textbox(label="Assistant Response", placeholder="Enter assistant response here", lines=2)
+        model_input = gr.Textbox(label="Model", value="gpt-4o")  # Default model is gpt-4o
+
+        # Output
+        output = gr.Textbox(label="Response", interactive=False)
+        
+        # Button to send inputs to the model and get a response
+        submit_btn = gr.Button("Get Response")
+
+        # When the button is clicked, interact with the Space and display the result
+        submit_btn.click(interact_with_space, 
+                         inputs=[system_prompt_input, user_prompt_input, assistant_response_input, model_input], 
+                         outputs=[output])
+
+    return demo
+
+# Launch the Gradio UI
+ui = create_ui()
+ui.launch()