app.py

import json
import uuid
import requests
import streamlit as st

# Set up page configuration
st.set_page_config(
    page_title="SlimFit Coach",
    layout="wide",
    page_icon="🌊",
)

# Generate or load existing session ID
if "id" not in st.session_state:
    st.session_state.id = str(uuid.uuid4()).lower()

# Title of the app
st.title("SlimFit Coach")

# Sidebar customization options
st.sidebar.title("SlimFit Coach Settings")

# Default Messages Section
with st.sidebar.expander("Default Messages", expanded=True):
    welcome_message = st.text_area(
        "Welcome Message",
        value="Hello! I’m SlimFit Coach, your personal weight loss coach. How can I assist you on your journey to achieving your weight loss goals?",
        height=100,
    )

    # Default Question Section
    with st.sidebar.expander("Default Question", expanded=True):
        if st.button("Add Question"):
            st.session_state.default_question = st.text_area(
                "Question",
                value='''- "Objective: What are the main weight loss goals you're aiming to achieve? (For example, specific weight loss target, fitness improvement, etc.?)"''',
                height=200,
            )

# Coaching Style Section
with st.sidebar.expander("Coaching Style", expanded=True):

    # Function to create dual-label sliders with total 100
    def dual_slider(label_left, label_right, default_val):
        slider_val = st.slider(f"{label_left} ↔ {label_right}", 0, 100, default_val)
        return slider_val, 100 - slider_val

    # Sliders for promptValues parameters
    question_val, advice_val = dual_slider("Question", "Advice", 50)
    gentle_val, direct_val = dual_slider("Gentle", "Direct", 50)
    short_val, long_val = dual_slider("Short", "Long", 50)
    accepting_val, challenging_val = dual_slider("Accepting", "Challenging", 50)
    serious_val, light_hearted_val = dual_slider("Serious", "Light hearted", 50)

    # Display the calculated values for verification (Optional)
    st.markdown(f"**Question**: {question_val}, **Advice**: {advice_val}")
    st.markdown(f"**Gentle**: {gentle_val}, **Direct**: {direct_val}")
    st.markdown(f"**Short**: {short_val}, **Long**: {long_val}")
    st.markdown(f"**Accepting**: {accepting_val}, **Challenging**: {challenging_val}")
    st.markdown(f"**Serious**: {serious_val}, **Light hearted**: {light_hearted_val}")

# Main chat-like interface
API_URL = "https://startrz-ai-agent.hf.space/api/v1/prediction/05225105-b77e-4366-b536-662139dc1e98" 
# Function to query the new API
def query(payload):
    try:
        response = requests.post(API_URL, json=payload)
        response.raise_for_status()  # Raise an exception for HTTP errors
        return response.json()
    except requests.exceptions.RequestException as e:
        return {"error": str(e)}

# Initialize session state for messages if not already set
if "messages" not in st.session_state:
    st.session_state.messages = []

# Display previous messages
for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

# Handle new user input
if prompt := st.chat_input("Message SlimFit Coach"):
    # Append user message to session state
    st.session_state.messages.append({"role": "user", "content": prompt})
    with st.chat_message("user"):
        st.markdown(prompt)
    # Placeholder for AI response
    with st.spinner(text='Querying SlimFit Coach...'):
        with st.chat_message("assistant"):
            message_placeholder = st.empty()

            payload = {
                "question": prompt,
                "overrideConfig": {
                    "sessionId": st.session_state.id,
                    "promptValues": {
                        "text": "{{question}}",
                        "question": question_val,
                        "advice": advice_val,
                        "gentle": gentle_val,
                        "direct": direct_val,
                        "short": short_val,
                        "long": long_val,
                        "accepting": accepting_val,
                        "challenging": challenging_val,
                        "serious": serious_val,
                        "light_hearted": light_hearted_val,
                        "welcome_message": welcome_message,
                        "default_question": st.session_state.default_question,
                    }
                }
            }

            # Generate response from the new API
            response = query(payload)

            # Parse the JSON response
            text = response.get("text", "Sorry, I couldn't understand the response.")

            # Display the AI response
            message_placeholder.markdown(text)
            # Append AI message to session state
            st.session_state.messages.append({"role": "assistant", "content": text})