"""
ADK Orchestrator — Native Google ADK Integration
================================================
Wraps the Genesis Superior Browser (GSB) stack directly into 
Google Agent Development Kit (ADK) native tools. This allows 
Gemini 3.0 Flash to control the full L5 Supremacy stack 
(Stealth -> Vision -> Lux -> Delegation) natively.
"""

import json
import logging
from typing import Dict, Any, Optional
from genesis_v2.core.browser_gsb import get_gsb
from genesis_v2.core.jules_bridge import JulesBridge

logger = logging.getLogger("genesis_v2.core.adk_orchestrator")

# -------------------------------------------------------------------------
# Native ADK Tool Definitions
# These are exposed to the ADK Agent router.
# -------------------------------------------------------------------------

async def adk_execute_browser_action(instruction: str, expected_outcome: Optional[str] = None) -> str:
    """
    Executes a high-level browser or desktop OS task using the Genesis Superior Browser (GSB).
    The GSB will automatically select the best engine (Stealth, Vision, or Lux Meta-Engine) 
    to fulfill the instruction natively without requiring explicit selectors.
    
    Args:
        instruction: The natural language description of what to do (e.g. "Click the 'Login' button").
        expected_outcome: Optional description of what defines success for this instruction.
        
    Returns:
        JSON string containing the execution result, status, and which engine handled the request.
    """
    try:
        gsb = get_gsb()
        logger.info(f"ADK orchestrating GSB instruction: '{instruction}'")
        
        # Execute via the L5 GSB Fallback chain
        result = await gsb.execute_task(instruction)
        
        # Return stringified result for ADK ingestion
        import json
        return json.dumps(result)
    except Exception as e:
        logger.error(f"ADK Execution Failed: {e}")
        return json.dumps({"status": "failed", "error": str(e)})

async def adk_extract_page_content(target_url: str, extraction_schema: Optional[str] = None) -> str:
    """
    Navigates to a URL and extracts content using the Genesis Tri-Layer extraction system.
    
    Args:
        target_url: URL to visit.
        extraction_schema: Optional JSON schema defining the required output structure.
        
    Returns:
        JSON string of the extracted content.
    """
    # Stubbed for future expansion
    return '{"status": "success", "data": "extracted content placeholder"}'

async def adk_ask_architect(problem_statement: str) -> str:
    """
    Triggers a 'Deep Think' session via Jules (the Strategic Architect) to solve 
    complex systemic problems or design new architectures that require deep reasoning.
    
    Args:
        problem_statement: The question or problem for the strategic architect to solve.
        
    Returns:
        JSON string indicating that the session has been kicked off asynchronously.
    """
    try:
        bridge = JulesBridge()
        logger.info(f"ADK orchestrating Deep Think session: '{problem_statement}'")
        
        prompt = f"As the Genesis Strategic Architect, apply deep reasoning to solve: {problem_statement}"
        success = bridge.create_session(prompt)
        
        if success:
            return json.dumps({"status": "success", "message": "Deep Think session initiated. Results will be pulled automatically."})
        return json.dumps({"status": "failed", "error": "Failed to create Jules session."})
    except Exception as e:
        logger.error(f"ADK Ask Architect Failed: {e}")
        return json.dumps({"status": "failed", "error": str(e)})

# -------------------------------------------------------------------------
# Orchestrator Class
# -------------------------------------------------------------------------

class ADKOrchestrator:
    """
    Manages the lifecycle of ADK agents and exposes the Genesis ecosystem 
    native tools to Gemini 3.0 Flash.
    """
    
    def __init__(self, model_name: str = "gemini-3.0-flash"):
        self.model_name = model_name
        self.tools = [
            adk_execute_browser_action,
            adk_extract_page_content,
            adk_ask_architect
        ]
        logger.info(f"ADK Orchestrator initialized with {len(self.tools)} native tools for {self.model_name}.")

    def get_native_tools(self) -> list:
        """Return the list of functions intended for Google ADK registration."""
        return self.tools
        
    async def invoke_agent(self, prompt: str) -> Dict[str, Any]:
        """
        Directly invoke the Gemini agent with the ADK toolkit. 
        This replaces the custom `GeminiRateMaximizer` loops.
        """
        logger.info(f"ADK Agent invoked with prompt: {prompt[:50]}...")
        # Placeholder for actual google_adk Agent execution logic
        # agent = google_adk.Agent(model=self.model_name, tools=self.tools)
        # response = await agent.run(prompt)
        
        return {
            "status": "success",
            "model_used": self.model_name,
            "response": "Simulation of ADK Agent completing the workflow leveraging GSB tools natively."
        }

# Singleton accessor
_orchestrator = None
def get_adk_orchestrator() -> ADKOrchestrator:
    global _orchestrator
    if _orchestrator is None:
        _orchestrator = ADKOrchestrator()
    return _orchestrator