import gradio as gr
import pandas as pd
import os

# Load survey dataset from CSV
survey_data = None
try:
    if os.path.exists("survey.csv"):
        survey_data = pd.read_csv("survey.csv")
    else:
        # fallback fake dataset
        survey_data = pd.DataFrame({
            "employee": ["Aiman", "Ali", "Sara"],
            "mood": ["Positive", "Negative", "Neutral"],
            "recommendation": [
                "Keep up the good work!",
                "Take a short break to reduce stress.",
                "Encourage more collaboration."
            ]
        })
except Exception as e:
    print("Error loading CSV:", str(e))


def chatbot(query):
    try:
        if not query or query.strip() == "":
            return "⚠️ Please type a valid question."

        query_lower = query.lower()

        # Match employee name
        for i, row in survey_data.iterrows():
            if row["employee"].lower() in query_lower:
                return f"✅ {row['employee']} is feeling **{row['mood']}**.\n💡 Recommendation: {row['recommendation']}"

        # No match found
        return "ℹ️ I don’t have data for that person. Try asking about Aiman, Ali, or Sara."
    
    except Exception as e:
        return f"🚨 Error: {str(e)}"


# Gradio Chat Interface
iface = gr.ChatInterface(fn=chatbot, title="Pulse Survey Chatbot")
iface.launch()