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

# Email configuration
SENDER_EMAIL = "clen.emenike@gmail.com"  # Replace with your email
SENDER_PASSWORD = "Achuta@86"  # Replace with your email password
SMTP_SERVER = "smtp.gmail.com"  # Replace with your SMTP server
SMTP_PORT = 587  # Replace with your SMTP port

# Set up the open-source LLM
@st.cache_resource
def load_model():
    model_name = "google/flan-t5-large"
    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)}"

tools = [
    Tool(
        name="Send Email",
        func=send_email,
        description="Sends an email. Args: to_email, subject, body"
    )
]

prompt = PromptTemplate.from_template(
    """You are a helpful assistant scheduling cybersecurity program meetings. 
    Your task is to collect the user's name, email, and preferred meeting date, then send a meeting invitation.

    Use the following format:
    Human: <user's input>
    Assistant: <your response>
    Human: <user's input>
    Assistant: <your response>
    ...

    Once you have all the information, use the Send Email tool to send the invitation.
    The email should include this Zoom link: https://us04web.zoom.us/j/73793374638?pwd=S0TEJ30da7dhQ8viOdafMzPfCVzoLJ.1
    And this Meeting ID: 737 9337 4638

    Begin the conversation by asking for the user's name.

    {chat_history}
    Human: {input}
    Assistant: Let's proceed step by step:
    {agent_scratchpad}

    Tools available:
    {tools}

    Tool names:
    {tool_names}
    """
)

agent = create_react_agent(local_llm, tools, prompt)
agent_executor = AgentExecutor.from_agent_and_tools(
    agent=agent, tools=tools, verbose=True, memory=ConversationBufferMemory(memory_key="chat_history", return_messages=True)
)

# Streamlit interface
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..."):
            response = agent_executor.run(prompt)
            st.markdown(response)
            st.session_state.messages.append({"role": "assistant", "content": response})

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