import json
import logging
from datetime import datetime
from time import time
from typing import List

from core.edges import EntityEdge, EpisodicEdge
from core.llm_client import LLMClient
from core.nodes import EntityNode, EpisodicNode
from core.prompts import prompt_library
from core.utils.maintenance.temporal_operations import NodeEdgeNodeTriplet

logger = logging.getLogger(__name__)


def build_episodic_edges(
	entity_nodes: List[EntityNode],
	episode: EpisodicNode,
	created_at: datetime,
) -> List[EpisodicEdge]:
	edges: List[EpisodicEdge] = []

	for node in entity_nodes:
		edge = EpisodicEdge(
			source_node_uuid=episode.uuid,
			target_node_uuid=node.uuid,
			created_at=created_at,
		)
		edges.append(edge)

	return edges


async def extract_new_edges(
	llm_client: LLMClient,
	episode: EpisodicNode,
	new_nodes: list[EntityNode],
	relevant_schema: dict[str, any],
	previous_episodes: list[EpisodicNode],
) -> tuple[list[EntityEdge], list[EntityNode]]:
	# Prepare context for LLM
	context = {
		'episode_content': episode.content,
		'episode_timestamp': (episode.valid_at.isoformat() if episode.valid_at else None),
		'relevant_schema': json.dumps(relevant_schema, indent=2),
		'new_nodes': [{'name': node.name, 'summary': node.summary} for node in new_nodes],
		'previous_episodes': [
			{
				'content': ep.content,
				'timestamp': ep.valid_at.isoformat() if ep.valid_at else None,
			}
			for ep in previous_episodes
		],
	}

	llm_response = await llm_client.generate_response(prompt_library.extract_edges.v1(context))
	new_edges_data = llm_response.get('new_edges', [])
	logger.info(f'Extracted new edges: {new_edges_data}')

	# Convert the extracted data into EntityEdge objects
	new_edges = []
	for edge_data in new_edges_data:
		source_node = next(
			(node for node in new_nodes if node.name == edge_data['source_node']),
			None,
		)
		target_node = next(
			(node for node in new_nodes if node.name == edge_data['target_node']),
			None,
		)

		# If source or target is not in new_nodes, check if it's an existing node
		if source_node is None and edge_data['source_node'] in relevant_schema['nodes']:
			existing_node_data = relevant_schema['nodes'][edge_data['source_node']]
			source_node = EntityNode(
				uuid=existing_node_data['uuid'],
				name=edge_data['source_node'],
				labels=[existing_node_data['label']],
				summary='',
				created_at=datetime.now(),
			)
		if target_node is None and edge_data['target_node'] in relevant_schema['nodes']:
			existing_node_data = relevant_schema['nodes'][edge_data['target_node']]
			target_node = EntityNode(
				uuid=existing_node_data['uuid'],
				name=edge_data['target_node'],
				labels=[existing_node_data['label']],
				summary='',
				created_at=datetime.now(),
			)

		if (
			source_node
			and target_node
			and not (
				source_node.name.startswith('Message') or target_node.name.startswith('Message')
			)
		):
			valid_at = (
				datetime.fromisoformat(edge_data['valid_at'])
				if edge_data['valid_at']
				else episode.valid_at or datetime.now()
			)
			invalid_at = (
				datetime.fromisoformat(edge_data['invalid_at']) if edge_data['invalid_at'] else None
			)

			new_edge = EntityEdge(
				source_node=source_node,
				target_node=target_node,
				name=edge_data['relation_type'],
				fact=edge_data['fact'],
				episodes=[episode.uuid],
				created_at=datetime.now(),
				valid_at=valid_at,
				invalid_at=invalid_at,
			)
			new_edges.append(new_edge)
			logger.info(
				f'Created new edge: {new_edge.name} from {source_node.name} (UUID: {source_node.uuid}) to {target_node.name} (UUID: {target_node.uuid})'
			)

	affected_nodes = set()

	for edge in new_edges:
		affected_nodes.add(edge.source_node)
		affected_nodes.add(edge.target_node)
	return new_edges, list(affected_nodes)


async def extract_edges(
	llm_client: LLMClient,
	episode: EpisodicNode,
	nodes: list[EntityNode],
	previous_episodes: list[EpisodicNode],
) -> list[EntityEdge]:
	start = time()

	# Prepare context for LLM
	context = {
		'episode_content': episode.content,
		'episode_timestamp': (episode.valid_at.isoformat() if episode.valid_at else None),
		'nodes': [
			{'uuid': node.uuid, 'name': node.name, 'summary': node.summary} for node in nodes
		],
		'previous_episodes': [
			{
				'content': ep.content,
				'timestamp': ep.valid_at.isoformat() if ep.valid_at else None,
			}
			for ep in previous_episodes
		],
	}

	llm_response = await llm_client.generate_response(prompt_library.extract_edges.v2(context))
	edges_data = llm_response.get('edges', [])

	end = time()
	logger.info(f'Extracted new edges: {edges_data} in {(end - start) * 1000} ms')

	# Convert the extracted data into EntityEdge objects
	edges = []
	for edge_data in edges_data:
		if edge_data['target_node_uuid'] and edge_data['source_node_uuid']:
			edge = EntityEdge(
				source_node_uuid=edge_data['source_node_uuid'],
				target_node_uuid=edge_data['target_node_uuid'],
				name=edge_data['relation_type'],
				fact=edge_data['fact'],
				episodes=[episode.uuid],
				created_at=datetime.now(),
				valid_at=None,
				invalid_at=None,
			)
			edges.append(edge)
			logger.info(
				f'Created new edge: {edge.name} from (UUID: {edge.source_node_uuid}) to (UUID: {edge.target_node_uuid})'
			)

	return edges


def create_edge_identifier(
	source_node: EntityNode, edge: EntityEdge, target_node: EntityNode
) -> str:
	return f'{source_node.name}-{edge.name}-{target_node.name}'


async def dedupe_extracted_edges_v2(
	llm_client: LLMClient,
	extracted_edges: list[NodeEdgeNodeTriplet],
	existing_edges: list[NodeEdgeNodeTriplet],
) -> list[NodeEdgeNodeTriplet]:
	# Create edge map
	edge_map = {}
	for n1, edge, n2 in existing_edges:
		edge_map[create_edge_identifier(n1, edge, n2)] = edge
	for n1, edge, n2 in extracted_edges:
		if create_edge_identifier(n1, edge, n2) in edge_map:
			continue
		edge_map[create_edge_identifier(n1, edge, n2)] = edge

	# Prepare context for LLM
	context = {
		'extracted_edges': [
			{'triplet': create_edge_identifier(n1, edge, n2), 'fact': edge.fact}
			for n1, edge, n2 in extracted_edges
		],
		'existing_edges': [
			{'triplet': create_edge_identifier(n1, edge, n2), 'fact': edge.fact}
			for n1, edge, n2 in extracted_edges
		],
	}
	logger.info(prompt_library.dedupe_edges.v2(context))
	llm_response = await llm_client.generate_response(prompt_library.dedupe_edges.v2(context))
	new_edges_data = llm_response.get('new_edges', [])
	logger.info(f'Extracted new edges: {new_edges_data}')

	# Get full edge data
	edges = []
	for edge_data in new_edges_data:
		edge = edge_map[edge_data['triplet']]
		edges.append(edge)

	return edges


async def dedupe_extracted_edges(
	llm_client: LLMClient,
	extracted_edges: list[EntityEdge],
	existing_edges: list[EntityEdge],
) -> list[EntityEdge]:
	# Create edge map
	edge_map = {}
	for edge in existing_edges:
		edge_map[edge.fact] = edge
	for edge in extracted_edges:
		if edge.fact in edge_map:
			continue
		edge_map[edge.fact] = edge

	# Prepare context for LLM
	context = {
		'extracted_edges': [{'name': edge.name, 'fact': edge.fact} for edge in extracted_edges],
		'existing_edges': [{'name': edge.name, 'fact': edge.fact} for edge in extracted_edges],
	}

	llm_response = await llm_client.generate_response(prompt_library.dedupe_edges.v1(context))
	new_edges_data = llm_response.get('new_edges', [])
	logger.info(f'Extracted new edges: {new_edges_data}')

	# Get full edge data
	edges = []
	for edge_data in new_edges_data:
		edge = edge_map[edge_data['fact']]
		edges.append(edge)

	return edges


async def dedupe_edge_list(
	llm_client: LLMClient,
	edges: list[EntityEdge],
) -> list[EntityEdge]:
	start = time()

	# Create edge map
	edge_map = {}
	for edge in edges:
		edge_map[edge.fact] = edge

	# Prepare context for LLM
	context = {'edges': [{'name': edge.name, 'fact': edge.fact} for edge in edges]}

	llm_response = await llm_client.generate_response(
		prompt_library.dedupe_edges.edge_list(context)
	)
	unique_edges_data = llm_response.get('unique_edges', [])

	end = time()
	logger.info(f'Extracted edge duplicates: {unique_edges_data} in {(end - start) * 1000} ms ')

	# Get full edge data
	unique_edges = []
	for edge_data in unique_edges_data:
		fact = edge_data['fact']
		unique_edges.append(edge_map[fact])

	return unique_edges