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| import streamlit as st | |
| import requests | |
| HF_BACKEND_URL = "https://your-backend-url.hf.space" # Update with your backend link | |
| st.title("π Plagiarism & AI Detector") | |
| # Function to safely call API | |
| def fetch_api_response(url, params=None, files=None): | |
| try: | |
| if files: | |
| response = requests.post(url, files=files) | |
| else: | |
| response = requests.post(url, params=params) | |
| if response.status_code == 200: | |
| return response.json() | |
| else: | |
| return {"error": f"API Error: {response.status_code} - {response.text}"} | |
| except requests.exceptions.RequestException as e: | |
| return {"error": f"Request Failed: {str(e)}"} | |
| # Text Plagiarism | |
| st.subheader("π Check Text Plagiarism") | |
| text = st.text_area("Enter text to check for plagiarism") | |
| if st.button("Check Plagiarism"): | |
| result = fetch_api_response(f"{HF_BACKEND_URL}/check_text", params={"text": text}) | |
| st.json(result) | |
| # Code Plagiarism | |
| st.subheader("π» Check Code Plagiarism") | |
| code = st.text_area("Paste code to check plagiarism") | |
| if st.button("Check Code Plagiarism"): | |
| result = fetch_api_response(f"{HF_BACKEND_URL}/check_code", params={"code": code}) | |
| st.json(result) | |
| # AI Detection | |
| st.subheader("π€ Detect AI-Generated Content") | |
| ai_text = st.text_area("Enter text to check AI detection") | |
| if st.button("Detect AI"): | |
| result = fetch_api_response(f"{HF_BACKEND_URL}/detect_ai", params={"text": ai_text}) | |
| st.json(result) | |
| # PDF Upload | |
| st.subheader("π Upload PDF for Plagiarism Check") | |
| pdf = st.file_uploader("Upload a PDF file", type=["pdf"]) | |
| if pdf: | |
| files = {"file": pdf.getvalue()} | |
| result = fetch_api_response(f"{HF_BACKEND_URL}/upload_pdf", files=files) | |
| st.json(result) | |