app.py

import streamlit as st
from agents.use_case_agent import get_use_case_agent
from agents.architecture_agent import get_architecture_agent
from langchain.agents import initialize_agent, AgentType
from langchain.llms import OpenAI

st.set_page_config(page_title="Wearable Diabetic Support AI Agents", layout="wide")
st.title("🧠 Wearable Diabetic Support System - Multi-Agent Simulator")

st.markdown("This app runs two LangChain-based AI agents:")
st.markdown("- 🧠 **Use Case Generator**")
st.markdown("- 🏗️ **Logical Architecture Generator**")

with st.sidebar:
    st.header("Model Settings")
    openai_api_key = st.text_input("Enter your OpenAI API Key", type="password")
    temperature = st.slider("Model Temperature", 0.0, 1.0, 0.0)

# Input Configuration
st.header("📋 System Configuration")
tasks = st.multiselect("Select Tasks", ["DietManagement", "ExerciseManagement", "MedicationManagement"], default=["DietManagement", "ExerciseManagement"])
environments = st.multiselect("Select Environments", ["Home", "Outdoor"], default=["Home"])
actors = st.multiselect("Select Actors", ["Patient", "Caregiver"], default=["Patient"])

if st.button("▶️ Run Agents"):
    if not openai_api_key:
        st.error("Please enter your OpenAI API key in the sidebar.")
    else:
        llm = OpenAI(temperature=temperature, openai_api_key=openai_api_key)

        # Initialize Agents
        use_case_tool = get_use_case_agent(llm)
        architecture_tool = get_architecture_agent(llm)

        # Run Use Case Agent
        st.subheader("🧠 Use Case Output")
        use_case_input = f"Define use cases for tasks: {tasks}, environments: {environments}, actors: {actors}"
        use_case_output = use_case_tool.run(use_case_input)
        st.code(use_case_output, language="markdown")

        # Run Architecture Agent
        st.subheader("🏗️ Logical Architecture Output")
        functions = [
            "LogMeal", "MonitorGlucose", "AnalyzeDiet", "ProvideDietFeedback",
            "TrackActivity", "AnalyzeActivity", "ProvideExerciseFeedback",
            "SendMedicationReminder", "LogMedicationIntake"
        ]
        arch_input = f"Define architecture with these functions: {functions}"
        arch_output = architecture_tool.run(arch_input)
        st.code(arch_output, language="markdown")