import streamlit as st
import requests
import torch
from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM

# Shopify API credentials
ACCESS_TOKEN = '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'
SHOP_NAME = '6znwwf-77.myshopify.com'

# Use a pipeline as a high-level helper for SQL generation
sql_generation_pipe = pipeline("text-generation", model="defog/sqlcoder-7b-2")

def generate_sql(natural_language_query):
    """Convert natural language to SQL query using a pipeline."""
    input_prompt = f"Convert the following query to SQL:\n{natural_language_query}"
    generated_sql = sql_generation_pipe(input_prompt, max_length=512)[0]['generated_text']
    return generated_sql

def fetch_data_from_shopify(endpoint, params):
    """Fetch data from Shopify API based on endpoint and parameters."""
    headers = {
        'X-Shopify-Access-Token': ACCESS_TOKEN,
        'Content-Type': 'application/json'
    }
    url = f"https://{SHOP_NAME}/admin/api/2023-10/{endpoint}.json"
    response = requests.get(url, headers=headers, params=params)
    
    if response.status_code == 200:
        return response.json()
    else:
        return {"error": f"Error fetching data: {response.status_code} - {response.text}"}

def sql_to_api_params(sql_query):
    """Convert SQL query into API parameters."""
    if "SELECT" in sql_query and "FROM" in sql_query:
        parts = sql_query.split("WHERE")
        if len(parts) == 2:
            conditions = parts[1].strip()
            condition_parts = conditions.split("=")
            if len(condition_parts) == 2:
                param_name = condition_parts[0].strip().replace(" ", "").lower()
                param_value = condition_parts[1].strip().strip('"')
                
                params = {param_name: param_value}
                return params
    return {}

# Streamlit application
st.title("Shopify SQL Query Interface")

user_input = st.text_input("Enter your query (e.g., 'Show me products of type Nilesh'):")

if st.button("Submit"):
    if user_input:
        # Generate SQL query from natural language
        sql_query = generate_sql(user_input)
        st.write(f"Generated SQL Query: {sql_query}")

        # Convert SQL query to API parameters
        params = sql_to_api_params(sql_query)
        st.write(f"API Parameters: {params}")

        # Fetch data from Shopify
        if params:
            products = fetch_data_from_shopify("products", params)
            st.write("Results:")
            st.json(products)
        else:
            st.warning("Could not convert SQL query to API parameters.")
    else:
        st.warning("Please enter a query.")