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| 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() |