import gspread
from google.oauth2.service_account import Credentials
import json
import os
from datetime import datetime
import streamlit as st

class FeedbackManager:
    def __init__(self):
        self.client = None
        self.sheet = None
        self.worksheet = None
        self._initialize_google_sheets()
    
    def _initialize_google_sheets(self):
        """Initialize Google Sheets connection"""
        try:
            # Get credentials from environment variable or file
            creds_json = os.getenv("GOOGLE_SHEETS_CREDENTIALS")
            sheet_id = os.getenv("GOOGLE_SHEETS_ID")
            
            if not creds_json or not sheet_id:
                st.warning("⚠️ Google Sheets credentials not configured. Feedback will not be saved.")
                return
            
            # Parse credentials
            if creds_json.startswith('{'):
                # JSON string in environment variable
                creds_dict = json.loads(creds_json)
            else:
                # File path
                with open(creds_json, 'r') as f:
                    creds_dict = json.load(f)
            
            # Define the scope
            scope = [
            'https://www.googleapis.com/auth/spreadsheets',
            'https://www.googleapis.com/auth/drive'
            ]
            
            
            # Create credentials object
            credentials = Credentials.from_service_account_info(creds_dict, scopes=scope)
            
            # Initialize the client
            self.client = gspread.authorize(credentials)
            
            # Open the spreadsheet
            self.sheet = self.client.open_by_key(sheet_id)
            
            # Get or create the feedback worksheet
            try:
                self.worksheet = self.sheet.worksheet("Feedback")
            except gspread.WorksheetNotFound:
                # Create the worksheet with headers
                self.worksheet = self.sheet.add_worksheet(title="Feedback", rows="1000", cols="15")
                headers = [
                    "Timestamp",
                    "User Query", 
                    "AI Response",
                    "Source Rating (1-5)",
                    "Answer Rating (1-5)",
                    "Q1: Mistakes/Missing Info",
                    "Q2: Correct Answer",
                    "Q3: Thought Process",
                    "Embedder Model",
                    "LLM Model",
                    "Temperature",
                    "Top P",
                    "Max Length"
                ]
                self.worksheet.append_row(headers)
            
            # Get or create the conversation log worksheet
            try:
                self.conversation_worksheet = self.sheet.worksheet("Conversations")
            except gspread.WorksheetNotFound:
                # Create the worksheet with headers
                self.conversation_worksheet = self.sheet.add_worksheet(title="Conversations", rows="1000", cols="10")
                headers = [
                    "Timestamp",
                    "Session ID",
                    "User Query", 
                    "AI Response",
                    "Embedder Model",
                    "LLM Model",
                    "Temperature",
                    "Top P",
                    "Max Length",
                    "Response Time (seconds)"
                ]
                self.conversation_worksheet.append_row(headers)
            
        except Exception as e:
            st.error(f"❌ Failed to initialize Google Sheets: {str(e)}")
            self.client = None
            self.conversation_worksheet = None
    
    def save_feedback(self, user_query, ai_response, source_rating, answer_rating, 
                     feedback_q1,
                     embedder_model, llm_model, temperature, top_p, max_length):
        """Save feedback data to Google Sheets"""
        if not self.worksheet:
            st.error("❌ Google Sheets not initialized. Cannot save feedback.")
            return False
        
        try:
            timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
            
            # Truncate long responses to fit in Google Sheets cells
            ai_response_truncated = ai_response[:1000] + "..." if len(ai_response) > 1000 else ai_response
            feedback_q1_truncated = feedback_q1[:500] + "..." if len(feedback_q1) > 500 else feedback_q1
            
            row = [
                timestamp,
                user_query,
                ai_response_truncated,
                source_rating if source_rating is not None else "",
                answer_rating if answer_rating is not None else "",
                feedback_q1_truncated,
                embedder_model,
                llm_model,
                temperature,
                top_p,
                max_length
            ]
            
            self.worksheet.append_row(row)
            return True
            
        except Exception as e:
            st.error(f"❌ Failed to save feedback: {str(e)}")
            return False
    
    def is_connected(self):
        """Check if Google Sheets connection is available"""
        return self.client is not None and self.worksheet is not None
    
    def log_conversation(self, session_id, user_query, ai_response, 
                        embedder_model, llm_model, temperature, top_p, max_length, response_time):
        """Log conversation data to Google Sheets"""
        if not hasattr(self, 'conversation_worksheet') or not self.conversation_worksheet:
            print("⚠️ Google Sheets conversation logging not initialized. Skipping log.")
            return False
        
        try:
            timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
            
            # Truncate long responses to fit in Google Sheets cells
            user_query_truncated = user_query[:500] + "..." if len(user_query) > 500 else user_query
            ai_response_truncated = ai_response[:1000] + "..." if len(ai_response) > 1000 else ai_response
            
            row = [
                timestamp,
                session_id,
                user_query_truncated,
                ai_response_truncated,
                embedder_model,
                llm_model,
                temperature,
                top_p,
                max_length,
                round(response_time, 2)
            ]
            
            self.conversation_worksheet.append_row(row)
            return True
            
        except Exception as e:
            print(f"❌ Failed to log conversation: {str(e)}")
            return False