app.py

import streamlit as st
import os
import requests

st.set_page_config(page_title="Stakeholder Behaviour AI", layout="wide")

st.title("📊 AI Assistant for Stakeholder Behaviour in Civil Projects")

# Sidebar input
st.sidebar.header("Enter Situation / Stakeholder Statement")
user_input = st.sidebar.text_area("Describe the situation", height=150)

api_key = os.environ.get("apikeygpt")
if not api_key:
    st.error("GROQ_API_KEY environment variable not set in Hugging Face Space.")
else:
    if st.sidebar.button("Analyze Situation"):
        with st.spinner("Analyzing stakeholder behaviour..."):
            prompt = f"""
You are an expert AI in predicting stakeholder behaviour in civil engineering projects.

A user will give you a technical term, a stakeholder statement, or a project situation.

Your main job is to **predict stakeholder behaviours in the given situation,
describe likely consequences of those behaviours, identify the drivers
behind those behaviours, and provide strategies to influence them positively.**

Structure your report with the following sections:

1️⃣ Explanation  
2️⃣ Past Cases & Lessons Learned  
3️⃣ Stakeholder Classification  
4️⃣ Predicted Stakeholder Behaviours (with probability / likelihood)  
5️⃣ Behavioural Drivers (reasons for those behaviours)  
6️⃣ Behaviour Change Triggers (what could shift the behaviour)  
7️⃣ Potential Consequences of These Behaviours  
8️⃣ Risk & Impact Assessment  
9️⃣ Recommended Actions & Communication Strategy  
🔟 Behaviour Mitigation / Influence Strategies  
1️⃣1️⃣ Urgency Flag  
1️⃣2️⃣ Best Practices / References  

Respond in a professional but beginner-friendly tone, using bullet points where helpful.

Input from user:
{user_input}
"""

            headers = {
                "Authorization": f"Bearer {api_key}",
                "Content-Type": "application/json"
            }

            payload = {
                "model": "openai/gpt-oss-20B",  # updated model
                "messages": [{"role": "user", "content": prompt}],
                "temperature": 0.3
            }

            response = requests.post(
                "https://api.groq.com/openai/v1/chat/completions",
                headers=headers,
                json=payload
            )

            if response.status_code == 200:
                result = response.json()["choices"][0]["message"]["content"]
                st.markdown("### 📝 Analysis Result")
                st.write(result)
            else:
                st.error(f"API Error: {response.text}")