Update app.py
Browse files
app.py
CHANGED
@@ -1,47 +1,187 @@
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import streamlit as st
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from openai import OpenAI
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# Setting up the Streamlit page configuration
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st.set_page_config(page_title="StreamlitChatMessageHistory", page_icon="💬")
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st.title("Chatbot")
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# Initialize session state variables
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st.session_state.setup_complete = False
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st.session_state.user_message_count = 0
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st.session_state.chat_complete = False
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st.session_state.messages = []
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st.session_state["openai_model"] = "gpt-4o"
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# Helper functions to update session state
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def complete_setup():
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# # Setup stage for collecting user details
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# if not st.session_state.setup_complete:
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# st.subheader('Personal Information')
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# # Get personal information input
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# st.session_state["name"] = st.text_input(label="Name", value="",
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# # Company and Position Section
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# st.subheader('Company and Position')
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#
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#
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#
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# st.session_state["company"] = st.selectbox(
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# "Select a Company",
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# ("Amazon", "Meta", "Udemy", "365 Company", "Nestle", "LinkedIn", "Spotify"),
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# index=("Amazon", "Meta", "Udemy", "365 Company", "Nestle", "LinkedIn", "Spotify").index("
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# )
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# # Button to complete setup
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# if st.button("Start Interview", on_click=complete_setup):
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# st.write("Setup complete. Starting interview...")
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# Setup stage for collecting user details
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if not st.session_state.setup_complete:
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@@ -100,9 +240,9 @@ if not st.session_state.setup_complete:
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# Button to complete setup
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if st.button("Start Interview", on_click=complete_setup):
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st.write("Setup complete. Starting interview...")
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# Interview phase
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if st.session_state.setup_complete and not st.session_state.chat_complete:
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st.info(
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"""
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@@ -114,12 +254,18 @@ if st.session_state.setup_complete and not st.session_state.chat_complete:
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# Initialize OpenAI client
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client = OpenAI(api_key=st.secrets["OPENAI_API_KEY"])
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# Initializing the system prompt for the chatbot
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if not st.session_state.messages:
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st.session_state.messages = [{
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"role": "system",
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"content": (f"You are an HR that interviews {st.session_state['name']}
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f"{st.session_state['
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}]
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# Display chat messages
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@@ -140,7 +286,10 @@ if st.session_state.setup_complete and not st.session_state.chat_complete:
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with st.chat_message("assistant"):
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stream = client.chat.completions.create(
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model=st.session_state["openai_model"],
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messages=[
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stream=True,
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)
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response = st.write_stream(stream)
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@@ -151,4 +300,39 @@ if st.session_state.setup_complete and not st.session_state.chat_complete:
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# Check if the user message count reaches 5
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if st.session_state.user_message_count >= 5:
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st.session_state.chat_complete = True
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# import streamlit as st
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# from openai import OpenAI
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# # Setting up the Streamlit page configuration
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# st.set_page_config(page_title="StreamlitChatMessageHistory", page_icon="💬")
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# st.title("Chatbot")
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# # Initialize session state variables
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# st.session_state.setup_complete = False
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# st.session_state.user_message_count = 0
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# st.session_state.chat_complete = False
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# st.session_state.messages = []
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# st.session_state["openai_model"] = "gpt-4o"
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# # Helper functions to update session state
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# def complete_setup():
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# st.session_state.setup_complete = True
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# # # Setup stage for collecting user details
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# # if not st.session_state.setup_complete:
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# # st.subheader('Personal Information')
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# # # Get personal information input
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# # st.session_state["name"] = st.text_input(label="Name", value="", placeholder="Enter your name", max_chars=40)
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# # # Company and Position Section
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# # st.subheader('Company and Position')
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# # st.session_state["position"] = st.selectbox(
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# # "Choose a position",
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# # ("Data Scientist", "Data Engineer", "ML Engineer", "BI Analyst", "Financial Analyst"),
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# # index=("Data Scientist", "Data Engineer", "ML Engineer", "BI Analyst", "Financial Analyst").index("Data Scientist")
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# # )
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# # st.session_state["company"] = st.selectbox(
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# # "Select a Company",
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# # ("Amazon", "Meta", "Udemy", "365 Company", "Nestle", "LinkedIn", "Spotify"),
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# # index=("Amazon", "Meta", "Udemy", "365 Company", "Nestle", "LinkedIn", "Spotify").index("Amazon")
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# # )
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# # # Button to complete setup
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# # if st.button("Start Interview", on_click=complete_setup):
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# # st.write("Setup complete. Starting interview...")
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# # Setup stage for collecting user details
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# if not st.session_state.setup_complete:
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# st.subheader('Personal Information')
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# # Initialize session state for personal information
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# if "name" not in st.session_state:
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# st.session_state["name"] = ""
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# if "experience" not in st.session_state:
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# st.session_state["experience"] = ""
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# if "skills" not in st.session_state:
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# st.session_state["skills"] = ""
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# # Get personal information input
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# st.session_state["name"] = st.text_input(label="Name", value=st.session_state["name"], placeholder="Enter your name", max_chars=40)
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# st.session_state["experience"] = st.text_area(label="Experience", value=st.session_state["experience"], placeholder="Describe your experience", max_chars=200)
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# st.session_state["skills"] = st.text_area(label="Skills", value=st.session_state["skills"], placeholder="List your skills", max_chars=200)
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# # Company and Position Section
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# st.subheader('Company and Position')
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# # Initialize session state for company and position information and setting default values
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# if "level" not in st.session_state:
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# st.session_state["level"] = "Junior"
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# if "position" not in st.session_state:
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# st.session_state["position"] = "Data Scientist"
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# if "company" not in st.session_state:
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# st.session_state["company"] = "Amazon"
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# col1, col2 = st.columns(2)
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# with col1:
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# st.session_state["level"] = st.radio(
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# "Choose level",
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# key="visibility",
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# options=["Junior", "Mid-level", "Senior"],
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# index=["Junior", "Mid-level", "Senior"].index(st.session_state["level"])
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# )
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# with col2:
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# st.session_state["position"] = st.selectbox(
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# "Choose a position",
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# ("Data Scientist", "Data Engineer", "ML Engineer", "BI Analyst", "Financial Analyst"),
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# index=("Data Scientist", "Data Engineer", "ML Engineer", "BI Analyst", "Financial Analyst").index(st.session_state["position"])
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# )
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# st.session_state["company"] = st.selectbox(
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# "Select a Company",
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# ("Amazon", "Meta", "Udemy", "365 Company", "Nestle", "LinkedIn", "Spotify"),
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# index=("Amazon", "Meta", "Udemy", "365 Company", "Nestle", "LinkedIn", "Spotify").index(st.session_state["company"])
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# )
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# # Button to complete setup
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# if st.button("Start Interview", on_click=complete_setup):
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# st.write("Setup complete. Starting interview...")
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# # Interview phase
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# if st.session_state.setup_complete and not st.session_state.chat_complete:
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# st.info(
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# """
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# Start by introducing yourself
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# """,
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# icon="👋",
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# )
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# # Initialize OpenAI client
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# client = OpenAI(api_key=st.secrets["OPENAI_API_KEY"])
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# # Initializing the system prompt for the chatbot
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# if not st.session_state.messages:
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# st.session_state.messages = [{
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# "role": "system",
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# "content": (f"You are an HR that interviews {st.session_state['name']}. You should interview him for the "
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# f"{st.session_state['position']} position in the company {st.session_state['company']}")
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# }]
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# # Display chat messages
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# for message in st.session_state.messages:
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# if message["role"] != "system":
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# with st.chat_message(message["role"]):
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# st.markdown(message["content"])
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# # Handle user input and OpenAI response
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# # Put a max_chars limit
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# if st.session_state.user_message_count < 5:
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# if prompt := st.chat_input("Your response", max_chars=1000):
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# st.session_state.messages.append({"role": "user", "content": prompt})
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# with st.chat_message("user"):
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# st.markdown(prompt)
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# if st.session_state.user_message_count < 4:
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# with st.chat_message("assistant"):
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# stream = client.chat.completions.create(
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# model=st.session_state["openai_model"],
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# messages=[{"role": m["role"], "content": m["content"]} for m in st.session_state.messages],
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# stream=True,
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# )
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# response = st.write_stream(stream)
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# st.session_state.messages.append({"role": "assistant", "content": response})
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# # Increment the user message count
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# st.session_state.user_message_count += 1
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# # Check if the user message count reaches 5
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# if st.session_state.user_message_count >= 5:
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# st.session_state.chat_complete = True
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import streamlit as st
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from openai import OpenAI
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from streamlit_js_eval import streamlit_js_eval
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# Setting up the Streamlit page configuration
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st.set_page_config(page_title="StreamlitChatMessageHistory", page_icon="💬")
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st.title("Chatbot")
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# Initialize session state variables
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if "setup_complete" not in st.session_state:
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st.session_state.setup_complete = False
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if "user_message_count" not in st.session_state:
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st.session_state.user_message_count = 0
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if "feedback_shown" not in st.session_state:
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st.session_state.feedback_shown = False
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if "chat_complete" not in st.session_state:
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st.session_state.chat_complete = False
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if "messages" not in st.session_state:
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st.session_state.messages = []
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# Helper functions to update session state
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def complete_setup():
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st.session_state.setup_complete = True
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def show_feedback():
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st.session_state.feedback_shown = True
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# Setup stage for collecting user details
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if not st.session_state.setup_complete:
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# Button to complete setup
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if st.button("Start Interview", on_click=complete_setup):
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st.write("Setup complete. Starting interview...")
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# Interview phase
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if st.session_state.setup_complete and not st.session_state.feedback_shown and not st.session_state.chat_complete:
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st.info(
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"""
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# Initialize OpenAI client
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client = OpenAI(api_key=st.secrets["OPENAI_API_KEY"])
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# Setting OpenAI model if not already initialized
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if "openai_model" not in st.session_state:
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st.session_state["openai_model"] = "gpt-4o"
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# Initializing the system prompt for the chatbot
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if not st.session_state.messages:
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st.session_state.messages = [{
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"role": "system",
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"content": (f"You are an HR executive that interviews an interviewee called {st.session_state['name']} "
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f"with experience {st.session_state['experience']} and skills {st.session_state['skills']}. "
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f"You should interview him for the position {st.session_state['level']} {st.session_state['position']} "
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f"at the company {st.session_state['company']}")
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}]
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# Display chat messages
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with st.chat_message("assistant"):
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stream = client.chat.completions.create(
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model=st.session_state["openai_model"],
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messages=[
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{"role": m["role"], "content": m["content"]}
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for m in st.session_state.messages
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],
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stream=True,
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)
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response = st.write_stream(stream)
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# Check if the user message count reaches 5
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if st.session_state.user_message_count >= 5:
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st.session_state.chat_complete = True
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# Show "Get Feedback"
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if st.session_state.chat_complete and not st.session_state.feedback_shown:
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if st.button("Get Feedback", on_click=show_feedback):
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st.write("Fetching feedback...")
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# Show feedback screen
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if st.session_state.feedback_shown:
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st.subheader("Feedback")
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conversation_history = "\n".join([f"{msg['role']}: {msg['content']}" for msg in st.session_state.messages])
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# Initialize new OpenAI client instance for feedback
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feedback_client = OpenAI(api_key=st.secrets["OPENAI_API_KEY"])
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# Generate feedback using the stored messages and write a system prompt for the feedback
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feedback_completion = feedback_client.chat.completions.create(
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model="gpt-4o",
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messages=[
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{"role": "system", "content": """You are a helpful tool that provides feedback on an interviewee performance.
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Before the Feedback give a score of 1 to 10.
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Follow this format:
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Overal Score: //Your score
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Feedback: //Here you put your feedback
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Give only the feedback do not ask any additional questins.
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"""},
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{"role": "user", "content": f"This is the interview you need to evaluate. Keep in mind that you are only a tool. And you shouldn't engage in any converstation: {conversation_history}"}
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]
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)
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st.write(feedback_completion.choices[0].message.content)
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# Button to restart the interview
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337 |
+
if st.button("Restart Interview", type="primary"):
|
338 |
+
streamlit_js_eval(js_expressions="parent.window.location.reload()")
|