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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)
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