Update app.py

app.py

@@ -1,128 +1,78 @@
 import streamlit as st
-import smtplib
-from email.mime.text import MIMEText
-from email.mime.multipart import MIMEMultipart
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
-from langchain_huggingface import HuggingFacePipeline
-from langchain.agents import create_react_agent, AgentExecutor, Tool
-from langchain.prompts import PromptTemplate
-from langchain.memory import ConversationBufferMemory
-from langchain.schema import AgentAction, AgentFinish
-import concurrent.futures
-import time
-
-# Email configuration
-SENDER_EMAIL = "clen.emenike@gmail.com"
-SENDER_PASSWORD = "Achuta@86"
-SMTP_SERVER = "smtp.gmail.com"
-SMTP_PORT = 587
-
-@st.cache_resource
-def load_model():
-    model_name = "google/flan-t5-small"
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
-    model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
-    pipe = pipeline("text2text-generation", model=model, tokenizer=tokenizer, max_length=512)
-    return HuggingFacePipeline(pipeline=pipe)
-
-local_llm = load_model()
-
-def send_email(to_email, subject, body):
-    try:
-        message = MIMEMultipart()
-        message["From"] = SENDER_EMAIL
-        message["To"] = to_email
-        message["Subject"] = subject
-        message.attach(MIMEText(body, "plain"))
-        with smtplib.SMTP(SMTP_SERVER, SMTP_PORT) as server:
-            server.starttls()
-            server.login(SENDER_EMAIL, SENDER_PASSWORD)
-            server.send_message(message)
-        return "Email sent successfully"
-    except Exception as e:
-        return f"Failed to send email: {str(e)}"
-
-# Define tools before creating the agent
-tools = [Tool(name="Send Email", func=send_email, description="Sends an email. Args: to_email, subject, body")]
-
-# Define the prompt before creating the agent
-prompt = PromptTemplate.from_template(
-    """You are a helpful assistant scheduling cybersecurity program meetings. 
-    Collect the user's name, email, and preferred meeting date, then send a meeting invitation.
-    Begin by asking for the user's name if you don't have it.
-    Zoom link: https://us04web.zoom.us/j/73793374638?pwd=S0TEJ30da7dhQ8viOdafMzPfCVzoLJ.1
-    Meeting ID: 737 9337 4638
-
-    {chat_history}
-    Human: {input}
-    Assistant: Let's approach this step-by-step:
-    {agent_scratchpad}
-
-    Tools available:
-    {tools}
-
-    Tool names:
-    {tool_names}
-    """
-)
-
-# Create the agent after loading the model and defining tools and prompt
-agent = create_react_agent(local_llm, tools, prompt)
-
-# Create the AgentExecutor
-agent_executor = AgentExecutor.from_agent_and_tools(
-    agent=agent, 
-    tools=tools, 
-    verbose=True, 
-    memory=ConversationBufferMemory(memory_key="chat_history", return_messages=True),
-    handle_parsing_errors=True,
-    max_iterations=6,  # Limit the number of iterations
-    early_stopping_method="force"  # or "generate_until_stop"
-)
-
-def run_agent_with_timeout(executor, input_data, timeout):
-    with concurrent.futures.ThreadPoolExecutor() as pool:
-        future = pool.submit(executor, input_data)
-        try:
-            return future.result(timeout=timeout)
-        except concurrent.futures.TimeoutError:
-            raise TimeoutError("The operation timed out.")
-
-st.title("CyberSecurity Program Meeting Scheduler")
-st.write("Chat with the AI to schedule your meeting. The AI will ask for your name, email, and preferred meeting date.")
-
-if "messages" not in st.session_state:
-    st.session_state.messages = []
-
-for message in st.session_state.messages:
-    with st.chat_message(message["role"]):
-        st.markdown(message["content"])
-
-if prompt := st.chat_input("Your message"):
-    st.session_state.messages.append({"role": "user", "content": prompt})
-    with st.chat_message("user"):
-        st.markdown(prompt)
-
-    with st.chat_message("assistant"):
-        with st.spinner("Thinking..."):
-            try:
-                start_time = time.time()
-                response = run_agent_with_timeout(agent_executor, {"input": prompt}, timeout=15)
-                if isinstance(response, dict) and "output" in response:
-                    assistant_response = response["output"]
-                elif isinstance(response, (AgentAction, AgentFinish)):
-                    assistant_response = response.return_values.get("output", str(response))
-                else:
-                    assistant_response = str(response)
-                
-                st.markdown(assistant_response)
-                st.session_state.messages.append({"role": "assistant", "content": assistant_response})
-            except TimeoutError:
-                st.error("I apologize, but I'm having trouble processing your request at the moment. Could you please try asking your question again, or rephrase it?")
-            except Exception as e:
-                st.error(f"An error occurred: {str(e)}")
-
-st.sidebar.title("About")
-st.sidebar.info("This is an interactive CyberSecurity Program Meeting Scheduler. Chat with the AI to schedule your meeting. It will collect your information and send a meeting invitation via email.")
-
-# To run this script, use: streamlit run your_script_name.py
+from streamlit_elements import elements, mui, html, dashboard, sync
+
+# Function to render skills with progress bars
+def render_skill(skill_name, proficiency):
+    st.write(skill_name)
+    st.progress(proficiency / 100)  # Streamlit progress bar expects a value between 0 and 1
+
+# Main function to render the dashboard
+def app():
+    st.set_page_config(page_title="Recruitment Dashboard", layout="wide")
+    
+    # Personal Details Section
+    st.title("John Doe")
+    col1, col2 = st.columns([1, 3])
+    
+    with col1:
+        st.image("https://via.placeholder.com/100", width=100)
+    
+    with col2:
+        st.markdown("**Contact Information:**")
+        st.markdown("📧 johndoe@example.com")
+        st.markdown("📞 (123) 456-7890")
+        st.markdown("🔗 [linkedin.com/in/johndoe](https://linkedin.com/in/johndoe)")
+    
+    st.markdown("---")  # Horizontal line
+
+    # Skills Section
+    st.header("Skills")
+    col1, col2 = st.columns(2)
+    
+    with col1:
+        st.subheader("Hard Skills")
+        render_skill("Penetration Testing", 90)
+        render_skill("Network Security", 85)
+        render_skill("Incident Response", 80)
+        render_skill("Malware Analysis", 75)
+    
+    with col2:
+        st.subheader("Soft Skills")
+        render_skill("Critical Thinking", 90)
+        render_skill("Problem-Solving", 85)
+        render_skill("Communication", 80)
+        render_skill("Team Collaboration", 75)
+
+    st.markdown("---")  # Horizontal line
+
+    # Projects Section
+    st.header("Projects Delivered")
+    st.subheader("Simulated Network Intrusion and Defense")
+    st.write("Designed and executed a penetration testing strategy...")
+    st.markdown("**Tools Used:** Metasploit, Wireshark, Nmap")
+
+    st.markdown("---")  # Horizontal line
+
+    # Tools Proficiency Section
+    st.header("Tools Proficiency")
+    st.write("SIEM (Splunk, QRadar): Advanced")
+    st.write("Penetration Testing (Metasploit, Kali Linux): Advanced")
+    st.write("Network Analysis (Wireshark): Advanced")
+    st.write("Malware Analysis (Cuckoo Sandbox): Intermediate")
+    st.write("Cloud Security (AWS Security Hub): Intermediate")
+
+    st.markdown("---")  # Horizontal line
+
+    # Final Recommendation Section
+    st.header("Final Recommendation")
+    st.write("**Fit for Role:** Excellent")
+    st.write("**Recommended Action:** Highly recommended for interview.")
+    st.write("**Potential Areas for Development:** Further training in cloud security...")
+
+    # Action Button
+    if st.button("Schedule Interview"):
+        st.success("Interview scheduled!")
+
+# Run the app
+if __name__ == "__main__":
+    app()