Update app.py

app.py

@@ -1,14 +1,25 @@
 import gradio as gr
-from huggingface_hub import hf_hub_download
+from transformers import pipeline
 
-# Specify the model you want to use
+# Specify the model ID
 model_id = "Canstralian/CySec_Known_Exploit_Analyzer"
 
-# Assuming the model is a pipeline or has an interface, you can load it like this:
-# (This might need adjustment depending on the exact model type)
+# Load the model using Hugging Face's pipeline (adjust if needed)
+analyzer = pipeline("text-classification", model=model_id)
 
-# Load the model and interface from Hugging Face Hub
-model = gr.Interface.load(f"huggingface/{model_id}")
+# Define a function to process inputs using the model
+def analyze_exploit(text):
+    result = analyzer(text)
+    return result
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=analyze_exploit,
+    inputs=gr.Textbox(lines=2, placeholder="Enter exploit description..."),
+    outputs="json",
+    title="CySec Known Exploit Analyzer",
+    description="Analyze known cybersecurity exploits using a Hugging Face model."
+)
 
 # Launch the Gradio interface
-model.launch()
+interface.launch()