Update app.py

app.py

@@ -1,3 +1,238 @@
+# # app.py
+
+# import os
+# import re
+# import fitz  # PyMuPDF
+# import tempfile
+# import base64
+# from datetime import datetime
+# from gtts import gTTS
+# import streamlit as st
+# from transformers import pipeline
+# from groq import Groq
+
+# # ✅ Hugging Face and GROQ secrets loaded via Hugging Face Spaces Secrets interface
+
+# # ⛳ Access secrets securely from environment variables
+# GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+# HF_TOKEN = os.getenv("HF_TOKEN")
+# KAGGLE_USERNAME = os.getenv("KAGGLE_USERNAME")
+# KAGGLE_KEY = os.getenv("KAGGLE_KEY")
+
+# # ✅ Validate secrets
+# if not all([GROQ_API_KEY, HF_TOKEN, KAGGLE_USERNAME, KAGGLE_KEY]):
+#     st.error("❌ One or more required API keys are missing from the environment.")
+#     st.stop()
+
+# # ✅ Initialize Groq client
+# client = Groq(api_key=GROQ_API_KEY)
+
+# # ✅ Load phishing detection pipeline from Hugging Face
+# phishing_pipe = pipeline(
+#     "text-classification",
+#     model="ealvaradob/bert-finetuned-phishing",
+#     token=HF_TOKEN
+# )
+
+# # ✅ Language and role options
+# language_choices = ["English", "Urdu", "French"]
+# role_choices = ["Admin", "Procurement", "Logistics"]
+
+# # ✅ Glossary terms
+# GLOSSARY = {
+#     "phishing": "Phishing is a scam where attackers trick you into revealing personal information.",
+#     "malware": "Malicious software designed to harm or exploit systems.",
+#     "spam": "Unwanted or unsolicited messages.",
+#     "tone": "The emotional character of the message."
+# }
+
+# # ✅ Translations (demo dictionary-based)
+# TRANSLATIONS = {
+#     "Phishing": {"Urdu": "فشنگ", "French": "Hameçonnage"},
+#     "Spam": {"Urdu": "سپیم", "French": "Courrier indésirable"},
+#     "Malware": {"Urdu": "میلویئر", "French": "Logiciel malveillant"},
+#     "Safe": {"Urdu": "محفوظ", "French": "Sûr"}
+# }
+
+# # ✅ In-memory history and audio
+# if "history" not in st.session_state:
+#     st.session_state.history = []
+# if "audio_summary" not in st.session_state:
+#     st.session_state.audio_summary = ""
+
+# # =======================
+# # Streamlit UI
+# # =======================
+# st.set_page_config(page_title="ZeroPhish Gate", layout="wide")
+
+# st.title("🛡️ ZeroPhish Gate")
+# st.markdown("AI-powered phishing message detection and explanation.")
+
+# # Input fields
+# col1, col2 = st.columns([3, 1])
+# with col1:
+#     text_input = st.text_area("✉️ Paste Suspicious Message", height=200)
+#     uploaded_file = st.file_uploader("📄 Upload PDF/TXT (optional)", type=["pdf", "txt"])
+
+# with col2:
+#     language = st.selectbox("🌐 Preferred Language", language_choices)
+#     role = st.selectbox("🧑‍💼 Your Role", role_choices)
+
+# analyze_btn = st.button("🔍 Analyze with AI")
+# clear_btn = st.button("🗑️ Clear History")
+
+# # =======================
+# # Function Definitions
+# # =======================
+# def extract_text_from_file(file):
+#     if file is None:
+#         return ""
+#     ext = file.name.split(".")[-1].lower()
+#     if ext == "pdf":
+#         doc = fitz.open(stream=file.read(), filetype="pdf")
+#         return "\n".join(page.get_text() for page in doc)
+#     elif ext == "txt":
+#         return file.read().decode("utf-8")
+#     return ""
+
+# def analyze_with_huggingface(text):
+#     try:
+#         result = phishing_pipe(text)
+#         label = result[0]['label']
+#         confidence = round(result[0]['score'] * 100, 2)
+#         threat_type = {
+#             "PHISHING": "Phishing",
+#             "SPAM": "Spam",
+#             "MALWARE": "Malware",
+#             "LEGITIMATE": "Safe"
+#         }.get(label.upper(), "Unknown")
+#         return label, confidence, threat_type
+#     except Exception as e:
+#         return "Error", 0, f"Error: {e}"
+
+# def semantic_analysis(text):
+#     response = client.chat.completions.create(
+#         model="llama3-8b-8192",
+#         messages=[
+#             {"role": "system", "content": "You are a cybersecurity assistant."},
+#             {"role": "user", "content": f"Explain this suspicious message for a {role} in {language} without ending in questions:\n{text}"}
+#         ]
+#     )
+#     raw = response.choices[0].message.content
+#     clean = re.sub(r"Is there anything else you'd like.*", "", raw, flags=re.I).strip()
+#     return clean
+
+# def translate_label(threat_type):
+#     return TRANSLATIONS.get(threat_type, {}).get(language, threat_type)
+
+# def text_to_speech(text):
+#     try:
+#         tts = gTTS(text=text, lang='en')
+#         with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as fp:
+#             tts.save(fp.name)
+#             return fp.name
+#     except Exception as e:
+#         st.error(f"❌ Audio generation error: {e}")
+#         return None
+
+# def create_report(label, score, threat_type, explanation, text):
+#     ts = datetime.now().strftime("%Y%m%d_%H%M%S")
+#     filename = f"Zerophish_Report_{ts}.txt"
+#     report = f"""
+# 🔍 AI Threat Detection Report
+
+# Input Message:
+# {text}
+
+# Prediction: {label}
+# Threat Type: {threat_type}
+# Confidence: {score}%
+
+# ---
+
+# 🧠 Explanation:
+# {explanation}
+# """
+#     with open(filename, "w") as f:
+#         f.write(report)
+#     return filename
+
+# def render_history():
+#     with st.expander("🕓 View Analysis History", expanded=True):
+#         for i, record in enumerate(reversed(st.session_state.history)):
+#             with st.container():
+#                 st.markdown(f"**🔢 Entry #{len(st.session_state.history) - i}**")
+#                 st.markdown(f"**📝 Input:** {record['input'][:100]}...")
+#                 st.markdown(f"**🔐 Type:** {record['threat']} | **📊 Confidence:** {record['score']}%")
+#                 st.markdown(f"**📖 Summary:** {record['summary'][:200]}...")
+#                 st.markdown("---")
+
+# # =======================
+# # Run Analysis
+# # =======================
+# if clear_btn:
+#     st.session_state.history.clear()
+#     st.session_state.audio_summary = ""
+#     st.success("✅ History cleared!")
+
+# if analyze_btn:
+#     combined_text = text_input
+#     if uploaded_file:
+#         extracted = extract_text_from_file(uploaded_file)
+#         combined_text += "\n" + extracted
+
+#     if not combined_text.strip():
+#         st.warning("⚠️ Please enter some text or upload a file to analyze.")
+#     else:
+#         label, score, threat_type = analyze_with_huggingface(combined_text)
+#         translated_threat = translate_label(threat_type)
+
+#         st.subheader("🔍 AI Threat Detection Result")
+#         st.markdown(f"**Prediction:** {label}")
+#         st.markdown(f"**Threat Type:** {threat_type} ({translated_threat})")
+#         st.markdown(f"**Confidence:** {score}%")
+
+#         summary = ""
+#         if threat_type.lower() != "safe":
+#             with st.expander("🧠 Semantic Reanalysis by LLaMA"):
+#                 summary = semantic_analysis(combined_text)
+#                 st.write(summary)
+
+#                 st.session_state.audio_summary = summary  # Save for audio playback
+
+#                 audio_path = text_to_speech(summary)
+#                 if audio_path:
+#                     with open(audio_path, "rb") as f:
+#                         st.markdown("### 🔊 Audio Explanation")
+#                         st.audio(f.read(), format="audio/mp3")
+#                     os.remove(audio_path)
+
+#                 if st.button("📤 Send Report to IT"):
+#                     st.success("📨 Report sent to IT successfully.")
+
+#         # Save history
+#         st.session_state.history.append({
+#             "input": combined_text,
+#             "threat": threat_type,
+#             "score": score,
+#             "summary": summary
+#         })
+
+#         # Generate and offer download link
+#         if summary:
+#             report_path = create_report(label, score, threat_type, summary, combined_text)
+#             with open(report_path, "rb") as f:
+#                 b64 = base64.b64encode(f.read()).decode()
+#                 href = f'<a href="data:file/txt;base64,{b64}" download="{report_path}">📄 Download Full Report</a>'
+#                 st.markdown(href, unsafe_allow_html=True)
+
+#         with st.expander("📜 Glossary Help"):
+#             for term, definition in GLOSSARY.items():
+#                 st.markdown(f"**{term.capitalize()}**: {definition}")
+
+# render_history()
+
+
 # app.py
 
 import os
@@ -207,7 +442,7 @@ if analyze_btn:
                         st.audio(f.read(), format="audio/mp3")
                     os.remove(audio_path)
 
-                if st.button("📤 Send Report to IT"):
+                if st.button("📤 Report to IT"):
                     st.success("📨 Report sent to IT successfully.")
 
         # Save history
@@ -231,3 +466,4 @@ if analyze_btn:
                 st.markdown(f"**{term.capitalize()}**: {definition}")
 
 render_history()
+