import streamlit as st
import pandas as pd
import os
from datetime import datetime

st.set_page_config(page_title="BhashaKatha", layout="centered")

st.title("📚 BhashaKatha – Folk Tale & Proverb Collector")
st.write("Contribute a local proverb, folk tale, or historical memory in your native language.")

# Create or load the CSV file
DATA_FILE = "submissions.csv"
if os.path.exists(DATA_FILE):
    data = pd.read_csv(DATA_FILE)
else:
    data = pd.DataFrame(columns=["Timestamp", "Name", "Region", "Language", "Category", "Submission"])

# Form fields
with st.form("submission_form"):
    name = st.text_input("Your Name (Optional)", "")
    region = st.text_input("Region (Optional)", "")
    language = st.selectbox("Language", ["Hindi", "Tamil", "Telugu", "Kannada", "Odia", "Marathi", "Gujarati", "Punjabi", "Other"])
    category = st.selectbox("Category", ["Proverb", "Folk Tale", "Historical Memory"])
    submission = st.text_area("Enter your story or proverb here", height=200)

    submitted = st.form_submit_button("Submit")

    if submitted and submission.strip():
        new_data = {
            "Timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
            "Name": name.strip(),
            "Region": region.strip(),
            "Language": language,
            "Category": category,
            "Submission": submission.strip()
        }
        data = pd.concat([data, pd.DataFrame([new_data])], ignore_index=True)
        data.to_csv(DATA_FILE, index=False)
        st.success("✅ Thank you! Your contribution has been recorded.")

st.markdown("---")
st.subheader("📊 Corpus Contribution Stats")
st.write(f"Total Submissions Collected: **{len(data)}**")