app.py

import streamlit as st

def triage_checkin():
    st.write("### Triage and Check-in Expert 🚑")
    for i in range(1, 4):
        st.text_input(f"Question {i} for Triage")

def lab_analyst():
    st.write("### Lab Analyst 🧪")
    for i in range(1, 4):
        st.text_input(f"Question {i} for Lab Analysis")

def medicine_specialist():
    st.write("### Medicine Specialist 💊")
    for i in range(1, 4):
        st.text_input(f"Question {i} for Medicine")

def service_expert():
    st.write("### Service Expert 💲")
    for i in range(1, 4):
        st.text_input(f"Question {i} for Service")

def care_expert():
    st.write("### Level of Care Expert 🏥")
    for i in range(1, 4):
        st.text_input(f"Question {i} for Level of Care")

def terminology_expert():
    st.write("### Terminology Expert 📚")
    for i in range(1, 4):
        st.text_input(f"Question {i} for Terminology")

def cmo():
    st.write("### Chief Medical Officer 🩺")
    for i in range(1, 4):
        st.text_input(f"Question {i} for CMO")

def medical_director():
    st.write("### Medical Director Team 🏢")
    for i in range(1, 4):
        st.text_input(f"Question {i} for Medical Director")

def main():
    st.title("Mixture of Medical Experts Model")
    st.write("Harness the power of AI with this specialized healthcare framework! 🎉")
    st.write("#### In LLM Multi System Agents, we define a set of eight roles for achieving a mission, then benchmark performance across LLMs to find datasets with need alignment.")
    st.markdown("#### MTBench: https://huggingface.co/spaces/awacke1/MTBenchmarkForChatGPTMetricsScoring")

    role = st.selectbox("Select AI Role:", [
        "Triage and Check-in Expert",
        "Lab Analyst",
        "Medicine Specialist",
        "Service Expert",
        "Level of Care Expert",
        "Terminology Expert",
        "Chief Medical Officer",
        "Medical Director Team"
    ])

    if role == "Triage and Check-in Expert":
        triage_checkin()
    elif role == "Lab Analyst":
        lab_analyst()
    elif role == "Medicine Specialist":
        medicine_specialist()
    elif role == "Service Expert":
        service_expert()
    elif role == "Level of Care Expert":
        care_expert()
    elif role == "Terminology Expert":
        terminology_expert()
    elif role == "Chief Medical Officer":
        cmo()
    elif role == "Medical Director Team":
        medical_director()
    
    # Define Roles and their Descriptions
    roles = {
        "1. Coder": "💻 Creates short python code functions to solve tasks.",
        "2. Humanities Expert": "📚 Focuses on arts, literature, history, and other humanities subjects.",
        "3. Analyst": "🤔 Analyzes situations and provides logical solutions.",
        "4. Roleplay Expert": "🎭 Specialized in mimicking behaviors or characters.",
        "5. Mathematician": "➗ Solves mathematical problems with precision.",
        "6. STEM Expert": "🔬 Specialized in Science, Technology, Engineering, and Mathematics tasks.",
        "7. Extraction Expert": "🔍 Strictly sticks to facts and extracts concise information.",
        "8. Drafter": "📝 Exhibits expertise in generating textual content and narratives.",
    }
    
    # Streamlit UI
    st.title("AI Role Selector - CHARMSED 🤖✨")
    st.markdown("""
    ### Harness the power of AI with the CHARMSED framework. 
    #### This suite of roles brings together a comprehensive set of AI capabilities, tailored for diverse tasks:
    - **C**oder 💻: Craft pythonic solutions with precision.
    - **H**umanities Expert 📚: Dive deep into arts, literature, and history.
    - **A**nalyst 🤔: Derive insights through logical reasoning.
    - **R**oleplay Expert 🎭: Mimic behaviors or adopt personas for engaging interactions.
    - **M**athematician ➗: Crunch numbers and solve mathematical enigmas.
    - **S**TEM Expert 🔬: Navigate through the realms of Science, Technology, Engineering, and Mathematics.
    - **E**xtraction Expert 🔍: Extract concise information with a laser-focus.
    - **D**rafter 📝: Generate textual content and narratives with flair.
    Empower your tasks with the perfect AI role and unleash the magic of CHARMSED!
    """)
    
    # Dropdown to select role
    selected_role = st.selectbox("Select AI Role:", list(roles.keys()))
    
    # Display the description of the selected role
    st.write(roles[selected_role])
    
    # Switch to choose between two models
    model = st.radio("Choose Model:", ["model_1", "model_2"])
    
    # Text area for user input
    user_input = st.text_area("Provide your task/question:")
    
    # Button to execute
    if st.button("Execute"):
        # Here, you would add code to get the AI response based on the selected role and model.
        # For now, just echoing the user input.
        st.write(f"You said: {user_input}")

if __name__ == "__main__":
    main()