Update app.py

app.py

@@ -8,25 +8,20 @@ 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]"  # 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
+SENDER_EMAIL = "[email protected]"
+SENDER_PASSWORD = "Achuta@86"
+SMTP_SERVER = "smtp.gmail.com"
+SMTP_PORT = 587
 
-# Set up the open-source LLM
 @st.cache_resource
 def load_model():
-    model_name = "google/flan-t5-small"  # Changed from 'large' to 'small'
+    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
-    )
+    pipe = pipeline("text2text-generation", model=model, tokenizer=tokenizer, max_length=512)
     return HuggingFacePipeline(pipeline=pipe)
 
 local_llm = load_model()
@@ -38,7 +33,6 @@ def send_email(to_email, subject, body):
         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)
@@ -47,41 +41,18 @@ def send_email(to_email, subject, body):
     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"
-    )
-]
+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.
+    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 proceed step by step:
-    {agent_scratchpad}
-
-    Tools available:
-    {tools}
-
-    Tool names:
-    {tool_names}
+    Assistant: {agent_scratchpad}
     """
 )
 
@@ -91,12 +62,12 @@ agent_executor = AgentExecutor.from_agent_and_tools(
     tools=tools, 
     verbose=True, 
     memory=ConversationBufferMemory(memory_key="chat_history", return_messages=True),
-    handle_parsing_errors=True
+    handle_parsing_errors=True,
+    max_iterations=3,  # Limit the number of iterations
+    early_stopping_method="generate"  # Stop if the agent starts looping
 )
 
-# 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:
@@ -114,7 +85,8 @@ if prompt := st.chat_input("Your message"):
     with st.chat_message("assistant"):
         with st.spinner("Thinking..."):
             try:
-                response = agent_executor({"input": prompt})
+                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)):
@@ -124,6 +96,8 @@ if prompt := st.chat_input("Your message"):
                 
                 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)}")