#!/usr/bin/env python3
"""
Genesis Workspace Skill
=======================
Autonomous workflows for Google Workspace (Gmail, Docs, Sheets).

Features:
- Draft research summaries in Google Docs
- Compose grounded email responses in Gmail
- Extract data from Workspace sources
- MCP-compatible interface

Usage:
    from workspace_skill import WorkspaceAgent
    agent = WorkspaceAgent()
    agent.draft_summary("Genesis Audit", "Findings: ...")
"""

import os
import sys
import json
from datetime import datetime
from typing import List, Dict, Any

# Add genesis-system to path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

from search_grounding import SearchGroundedAgent

class WorkspaceAgent:
    """
    Agent that manages Google Workspace integrations.
    Acts as the hands for Genesis in the office productivity suite.
    """
    
    def __init__(self):
        self.grounded_agent = SearchGroundedAgent()
        print(f"[OK] Workspace Skill Initialized")
    
    def draft_summary(self, title: str, content: str) -> Dict[str, Any]:
        """
        Simulates drafting a report in Google Docs.
        In a full GCP environment, this would use the Google Docs API.
        """
        print(f"[WORK] Drafting Doc: {title}")
        
        # Refine content for "Professional Doc" tone
        prompt = f"Convert the following raw findings into a professionally formatted Google Doc structure with Title, Executive Summary, and Detailed Findings:\n\n{content}"
        refined = self.grounded_agent.query(prompt, use_grounding=False)
        
        return {
            "title": title,
            "doc_content": refined["response"],
            "status": "drafted_mcp",
            "timestamp": datetime.now().isoformat()
        }

    def compose_email(self, recipient: str, subject: str, context: str) -> Dict[str, Any]:
        """
        Simulates composing an email in Gmail.
        """
        print(f"[WORK] Composing Email to: {recipient}")
        
        prompt = f"Compose a professional email to {recipient} regarding '{subject}' based on this context: {context}"
        email = self.grounded_agent.query(prompt, use_grounding=False)
        
        return {
            "to": recipient,
            "subject": subject,
            "body": email["response"],
            "status": "drafted_in_gmail_mcp"
        }

if __name__ == "__main__":
    agent = WorkspaceAgent()
    print("[TEST] Workspace Skill Ready")
    # print(agent.compose_email("ceo@genesis.ai", "Mastery Report", "All Google services integrated."))