Update app.py

app.py

@@ -1,99 +1,99 @@
-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=("AIzaSyDQxZw2oDaD_UFjtW1Q0rx4yfSQivYrj58"))
-
-# 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
+
+load_dotenv()
+
+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)