"""
This module contains all graph-related routes for the LightRAG API.
"""

from typing import Optional, Dict, Any
from fastapi import APIRouter, Depends, Query, HTTPException
from pydantic import BaseModel

from ..utils_api import get_combined_auth_dependency

router = APIRouter(tags=["graph"])


class EntityUpdateRequest(BaseModel):
    entity_name: str
    updated_data: Dict[str, Any]
    allow_rename: bool = False


def create_graph_routes(rag, api_key: Optional[str] = None):
    combined_auth = get_combined_auth_dependency(api_key)

    @router.get("/graph/label/list", dependencies=[Depends(combined_auth)])
    async def get_graph_labels():
        """
        Get all graph labels

        Returns:
            List[str]: List of graph labels
        """
        return await rag.get_graph_labels()

    @router.get("/graphs", dependencies=[Depends(combined_auth)])
    async def get_knowledge_graph(
        label: str = Query(..., description="Label to get knowledge graph for"),
        max_depth: int = Query(3, description="Maximum depth of graph", ge=1),
        max_nodes: int = Query(1000, description="Maximum nodes to return", ge=1),
    ):
        """
        Retrieve a connected subgraph of nodes where the label includes the specified label.
        When reducing the number of nodes, the prioritization criteria are as follows:
            1. Hops(path) to the staring node take precedence
            2. Followed by the degree of the nodes

        Args:
            label (str): Label of the starting node
            max_depth (int, optional): Maximum depth of the subgraph,Defaults to 3
            max_nodes: Maxiumu nodes to return

        Returns:
            Dict[str, List[str]]: Knowledge graph for label
        """
        return await rag.get_knowledge_graph(
            node_label=label,
            max_depth=max_depth,
            max_nodes=max_nodes,
        )

    @router.get("/graph/entity/exists", dependencies=[Depends(combined_auth)])
    async def check_entity_exists(
        name: str = Query(..., description="Entity name to check"),
    ):
        """
        Check if an entity with the given name exists in the knowledge graph

        Args:
            name (str): Name of the entity to check

        Returns:
            Dict[str, bool]: Dictionary with 'exists' key indicating if entity exists
        """
        try:
            exists = await rag.chunk_entity_relation_graph.has_node(name)
            return {"exists": exists}
        except Exception as e:
            raise HTTPException(
                status_code=500, detail=f"Error checking entity existence: {str(e)}"
            )

    @router.post("/graph/entity/edit", dependencies=[Depends(combined_auth)])
    async def update_entity(request: EntityUpdateRequest):
        """
        Update an entity's properties in the knowledge graph

        Args:
            request (EntityUpdateRequest): Request containing entity name, updated data, and rename flag

        Returns:
            Dict: Updated entity information
        """
        try:
            print(request.entity_name, request.updated_data, request.allow_rename)
            result = await rag.aedit_entity(
                entity_name=request.entity_name,
                updated_data=request.updated_data,
                allow_rename=request.allow_rename,
            )
            return {
                "status": "success",
                "message": "Entity updated successfully",
                "data": result,
            }
        except ValueError as ve:
            raise HTTPException(status_code=400, detail=str(ve))
        except Exception as e:
            raise HTTPException(
                status_code=500, detail=f"Error updating entity: {str(e)}"
            )

    return router