Update app.py

app.py

@@ -1,29 +1,144 @@
+# 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
-import PyPDF2 as pdf
 from dotenv import load_dotenv
+import PyPDF2 as pdf
+import docx
+import chardet
 
 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())
+# 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'])
+
     return text
 
 # malware detection function
@@ -71,19 +186,19 @@ 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 Awaring yourself.")
+st.text("Use the AI system for malware detection and friendly conversation.")
 
 # 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.")
+    uploaded_file = st.file_uploader("Upload a file for malware detection", type=None, help="Please upload a file of any type.")
     submit_malware = st.button('Analyze for Malware')
     
     if submit_malware:
         if uploaded_file is not None:
-            text = input_pdf_text(uploaded_file)
+            text = read_file_content(uploaded_file)
             response = detect_malware(text)
             
             # Parse and display response in a structured way
@@ -100,3 +215,4 @@ with tab2:
             
             # Parse and display response in a structured way
             display_response_content(response)
+