"""
SurfSense deep agent implementation.

This module provides the factory function for creating SurfSense deep agents
with knowledge base search capability.
"""

from collections.abc import Sequence

from deepagents import create_deep_agent
from langchain_core.tools import BaseTool
from langchain_litellm import ChatLiteLLM
from sqlalchemy.ext.asyncio import AsyncSession

from app.agents.new_chat.context import SurfSenseContextSchema
from app.agents.new_chat.knowledge_base import create_search_knowledge_base_tool
from app.agents.new_chat.system_prompt import build_surfsense_system_prompt
from app.services.connector_service import ConnectorService

# =============================================================================
# Deep Agent Factory
# =============================================================================


def create_surfsense_deep_agent(
    llm: ChatLiteLLM,
    search_space_id: int,
    db_session: AsyncSession,
    connector_service: ConnectorService,
    user_instructions: str | None = None,
    enable_citations: bool = True,
    additional_tools: Sequence[BaseTool] | None = None,
):
    """
    Create a SurfSense deep agent with knowledge base search capability.

    Args:
        llm: ChatLiteLLM instance
        search_space_id: The user's search space ID
        db_session: Database session
        connector_service: Initialized connector service
        user_instructions: Optional user instructions to inject into the system prompt.
                          These will be added to the system prompt to customize agent behavior.
        enable_citations: Whether to include citation instructions in the system prompt (default: True).
                         When False, the agent will not be instructed to add citations to responses.
        additional_tools: Optional sequence of additional tools to inject into the agent.
                         The search_knowledge_base tool will always be included.

    Returns:
        CompiledStateGraph: The configured deep agent
    """
    # Create the search tool with injected dependencies
    search_tool = create_search_knowledge_base_tool(
        search_space_id=search_space_id,
        db_session=db_session,
        connector_service=connector_service,
    )

    # Combine search tool with any additional tools
    tools = [search_tool]
    if additional_tools:
        tools.extend(additional_tools)

    # Create the deep agent with user-configurable system prompt
    agent = create_deep_agent(
        model=llm,
        tools=tools,
        system_prompt=build_surfsense_system_prompt(
            user_instructions=user_instructions,
            enable_citations=enable_citations,
        ),
        context_schema=SurfSenseContextSchema,
    )

    return agent