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import streamlit as st
import pandas as pd
import duckdb
import requests
import re
import io
import os

# === πŸ” Safe API key input (streamlit secrets optional) ===
TOGETHER_API_KEY = os.environ.get("TOGETHER_API_KEY", "")  # Preferred for Hugging Face or env deployment

if not TOGETHER_API_KEY:
    TOGETHER_API_KEY = st.text_input("πŸ” Enter Together API Key", type="password")

# === SQL Generator Function ===
def generate_sql_from_prompt(prompt, df):
    schema = ", ".join([f"{col} ({str(dtype)})" for col, dtype in df.dtypes.items()])
    full_prompt = f"""
You are a SQL expert. Here is a table called 'df' with the following schema:
{schema}

User question: "{prompt}"

Write a valid SQL query using the 'df' table. Return only the SQL code.
"""
    url = "https://api.together.xyz/v1/chat/completions"
    headers = {
        "Authorization": f"Bearer {TOGETHER_API_KEY}",
        "Content-Type": "application/json"
    }
    payload = {
        "model": "mistralai/Mixtral-8x7B-Instruct-v0.1",
        "messages": [{"role": "user", "content": full_prompt}],
        "temperature": 0.2,
        "max_tokens": 200
    }

    response = requests.post(url, headers=headers, json=payload)
    response.raise_for_status()
    result = response.json()
    return result['choices'][0]['message']['content'].strip("```sql").strip("```").strip()

# === SQL Cleaner ===
def clean_sql_for_duckdb(sql, df_columns):
    sql = sql.replace("`", '"')
    for col in df_columns:
        if " " in col and f'"{col}"' not in sql:
            pattern = r'\b' + re.escape(col) + r'\b'
            sql = re.sub(pattern, f'"{col}"', sql)
    return sql

# === UI ===
st.set_page_config(page_title="🧠 Excel SQL Chatbot", layout="centered")
st.title("πŸ“Š Excel SQL Chatbot with LLM")
st.markdown("Upload your **Excel file**, ask a question in natural language, and get results via generated SQL.")

uploaded_file = st.file_uploader("πŸ“‚ Upload Excel file", type=["xlsx"])

if TOGETHER_API_KEY and uploaded_file:
    df = pd.read_excel(uploaded_file)
    st.success(f"βœ… Loaded: {uploaded_file.name} with shape {df.shape}")
    st.dataframe(df.head(), use_container_width=True)

    user_prompt = st.text_input("πŸ’¬ Ask a question about your data")

    if st.button("πŸš€ Generate SQL & Run") and user_prompt:
        try:
            sql_query = generate_sql_from_prompt(user_prompt, df)
            cleaned_sql = clean_sql_for_duckdb(sql_query, df.columns)

            st.code(sql_query, language="sql")

            con = duckdb.connect()
            con.register("df", df)
            result_df = con.execute(cleaned_sql).fetchdf()

            st.success("βœ… Query executed successfully")
            st.dataframe(result_df, use_container_width=True)

        except Exception as e:
            st.error(f"❌ Error: {e}")

elif not TOGETHER_API_KEY:
    st.warning("πŸ”‘ Please enter your Together API key to continue.")