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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 time
# Email configuration
SENDER_EMAIL = "[email protected]"
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)}"
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.
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: {agent_scratchpad}
"""
)
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),
handle_parsing_errors=True,
max_iterations=3, # Limit the number of iterations
early_stopping_method="generate" # Stop if the agent starts looping
)
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 = agent_executor({"input": prompt}, timeout=10) # 10-second timeout
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
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