Update app.py

app.py

@@ -1,144 +1,29 @@
-# import streamlit as st
-# import google.generativeai as genai
-# import os
-# import PyPDF2 as pdf
-# from dotenv import load_dotenv
-
-# load_dotenv()
-
-# genai.configure(api_key=("AIzaSyDziGvuT1woHnH4_S3L_zQZV55Yj-123A8"))
-
-# #alternative key
-# #genai.configure(api_key=("AIzaSyAr3d_7fp0wMxuUrnf_tATknu_TRPKDdxg"))
-
-# # gemini function for general content generation
-# def get_gemini_response(input):
-#     model = genai.GenerativeModel('gemini-pro')
-#     response = model.generate_content(input)
-#     return response
-
-# # convert pdf to text
-# def input_pdf_text(uploaded_file):
-#     reader = pdf.PdfReader(uploaded_file)
-#     text = ""
-#     for page in range(len(reader.pages)):
-#         page = reader.pages[page]
-#         text += str(page.extract_text())
-#     return text
-
-# # malware detection function
-# def detect_malware(input_text):
-#     malware_prompt = f"""
-#     ### As a cybersecurity expert, your task is to analyze the following text for any indications of malware.
-#     ### Text:
-#     {input_text}
-#     ### Analysis Output:
-#     1. Identify any potential malware-related content.
-#     2. Explain the reasoning behind your identification.
-#     3. Provide recommendations for mitigating any identified risks.
-#     """
-#     response = get_gemini_response(malware_prompt)
-#     return response
-
-# # chatbot function
-# def chatbot_response(user_input):
-#     chatbot_prompt = f"""
-#     ### You are an intelligent and friendly chatbot. Engage in a meaningful conversation with the user.
-#     ### User Input:
-#     {user_input}
-#     ### Chatbot Response:
-#     """
-#     response = get_gemini_response(chatbot_prompt)
-#     return response
-
-# # Function to parse and display response content
-# def display_response_content(response):
-#     st.subheader("Response Output")
-#     if response and response.candidates:
-#         response_content = response.candidates[0].content.parts[0].text if response.candidates[0].content.parts else ""
-#         sections = response_content.split('###')
-#         for section in sections:
-#             if section.strip():
-#                 section_lines = section.split('\n')
-#                 section_title = section_lines[0].strip()
-#                 section_body = '\n'.join(line.strip() for line in section_lines[1:] if line.strip())
-#                 if section_title:
-#                     st.markdown(f"**{section_title}**")
-#                 if section_body:
-#                     st.write(section_body)
-#     else:
-#         st.write("No response received from the model.")
-
-# ## Streamlit App
-# st.title("AI-Powered Security and Chatbot System")
-# st.text("Use the AI system for malware detection and Awaring yourself.")
-
-# # Tabs for different functionalities
-# tab1, tab2 = st.tabs(["Malware Detection", "Chatbot"])
-
-# with tab1:
-#     st.header("Malware Detection")
-#     uploaded_file = st.file_uploader("Upload a file for malware detection", type="pdf", help="Please upload a PDF file.")
-#     submit_malware = st.button('Analyze for Malware')
-    
-#     if submit_malware:
-#         if uploaded_file is not None:
-#             text = input_pdf_text(uploaded_file)
-#             response = detect_malware(text)
-            
-#             # Parse and display response in a structured way
-#             display_response_content(response)
-
-# with tab2:
-#     st.header("Chatbot")
-#     user_input = st.text_input("Type your message here")
-#     submit_chat = st.button('Send')
-
-#     if submit_chat:
-#         if user_input:
-#             response = chatbot_response(user_input)
-            
-#             # Parse and display response in a structured way
-#             display_response_content(response)
-
-
-
 import streamlit as st
 import google.generativeai as genai
 import os
-from dotenv import load_dotenv
 import PyPDF2 as pdf
-import docx
-import chardet
+from dotenv import load_dotenv
 
 load_dotenv()
 
 genai.configure(api_key=("AIzaSyDziGvuT1woHnH4_S3L_zQZV55Yj-123A8"))
 
+#alternative key
+#genai.configure(api_key=("AIzaSyAr3d_7fp0wMxuUrnf_tATknu_TRPKDdxg"))
+
 # gemini function for general content generation
 def get_gemini_response(input):
     model = genai.GenerativeModel('gemini-pro')
     response = model.generate_content(input)
     return response
 
-# Function to read text from different file types
-def read_file_content(uploaded_file):
-    file_type = uploaded_file.type
-    if file_type == "application/pdf":
-        reader = pdf.PdfReader(uploaded_file)
-        text = ""
-        for page in range(len(reader.pages)):
-            page = reader.pages[page]
-            text += str(page.extract_text())
-    elif file_type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
-        doc = docx.Document(uploaded_file)
-        text = '\n'.join([para.text for para in doc.paragraphs])
-    else:
-        # For other file types, assume it's a text file and try to read it as text
-        text = uploaded_file.read()
-        result = chardet.detect(text)
-        text = text.decode(result['encoding'])
-
+# convert pdf to text
+def input_pdf_text(uploaded_file):
+    reader = pdf.PdfReader(uploaded_file)
+    text = ""
+    for page in range(len(reader.pages)):
+        page = reader.pages[page]
+        text += str(page.extract_text())
     return text
 
 # malware detection function
@@ -186,19 +71,19 @@ def display_response_content(response):
 
 ## Streamlit App
 st.title("AI-Powered Security and Chatbot System")
-st.text("Use the AI system for malware detection and friendly conversation.")
+st.text("Use the AI system for malware detection and Awaring yourself.")
 
 # Tabs for different functionalities
 tab1, tab2 = st.tabs(["Malware Detection", "Chatbot"])
 
 with tab1:
     st.header("Malware Detection")
-    uploaded_file = st.file_uploader("Upload a file for malware detection", type=None, help="Please upload a file of any type.")
+    uploaded_file = st.file_uploader("Upload a file for malware detection", type="pdf", help="Please upload a PDF file.")
     submit_malware = st.button('Analyze for Malware')
     
     if submit_malware:
         if uploaded_file is not None:
-            text = read_file_content(uploaded_file)
+            text = input_pdf_text(uploaded_file)
             response = detect_malware(text)
             
             # Parse and display response in a structured way
@@ -216,3 +101,4 @@ with tab2:
             # Parse and display response in a structured way
             display_response_content(response)
 
+