Update app.py

app.py

@@ -1,3 +1,43 @@
 import gradio as gr
+import requests
 
-gr.Interface.load("models/vectara/hallucination_evaluation_model").launch()
+# Define the API parameters
+API_URL = "https://api-inference.huggingface.co/models/vectara/hallucination_evaluation_model"
+API_TOKEN = os.getenv("HF_AUTH_TOKEN")
+if not API_TOKEN:
+    raise ValueError("Please set the HF_AUTH_TOKEN environment variable.")
+
+headers = {"Authorization": f"Bearer {API_TOKEN}"}
+
+# Function to query the API
+def query(payload):
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()
+
+# Function to be called by the Gradio interface
+def evaluate_hallucination(input1, input2):
+    # Combine the inputs
+    combined_input = f"{input1}. {input2}"
+    
+    # Make the API call
+    output = query({"inputs": combined_input})
+    
+    # Extract the score from the output
+    score = output[0][0]['score']
+    
+    # Return a red or green circle based on the score
+    if score < 0.5:
+        return "🔴", "The score is less than 0.5"
+    else:
+        return "🟢", "The score is greater than 0.5"
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=evaluate_hallucination,
+    inputs=[gr.inputs.Textbox(label="Input 1"), gr.inputs.Textbox(label="Input 2")],
+    outputs=[gr.outputs.Label(), gr.outputs.Textbox(label="Explanation")],
+    live=False
+)
+
+# Launch the interface
+iface.launch()