Delete app.py

app.py

@@ -1,43 +0,0 @@
-import gradio as gr
-import requests
-import json
-
-# Define API keys (ensure these are securely handled and not exposed in public code repositories)
-API_KEY = "565c106133mshb641eb3210436aep10e7fbjsn9b12f087ae76"
-API_HOST = "ai-content-identifier2.p.rapidapi.com"
-
-# Code for Text AI Detect
-def text_check(user_input):
-    url = f"https://{API_HOST}/text"
-    payload = {
-        "text": user_input,
-        "threshold": 10  # Adjust this if needed to test different sensitivity levels
-    }
-    headers = {
-        "x-rapidapi-key": API_KEY,
-        "x-rapidapi-host": API_HOST,
-        "Content-Type": "application/json"
-    }
-    try:
-        response = requests.post(url, json=payload, headers=headers)
-        response.raise_for_status()  # Raises an HTTPError for bad responses
-        data = response.json()
-        # Format the output to be user-friendly
-        if 'success' in data and data['success']:
-            ai_status = 'Yes' if data['data']['ai'] else 'No'
-            return (f"AI Content Detected: {ai_status}\n"
-                    f"Confidence: {data['data']['percentage']}%\n"
-                    f"Total Words: {data['data']['stats']['totalWords']}\n"
-                    f"AI Words: {data['data']['stats']['aiWords']}\n"
-                    f"Human Words: {data['data']['stats']['humanWords']}\n"
-                    f"Note: {data['note']}")
-        else:
-            return "Failed to analyze text. Please try again."
-    except requests.exceptions.RequestException as e:
-        print(f"Error during API call: {e}")
-        return {"error": str(e)}
-
-demo = gr.Interface(fn=text_check, inputs="textbox", outputs="textbox")
-
-if __name__ == "_main_":
-    demo.launch()