from abc import ABC, abstractmethod from datetime import datetime from uuid import uuid1 from openai import OpenAI from pydantic import BaseModel, Field from neo4j import AsyncDriver import logging logger = logging.getLogger(__name__) class Node(BaseModel, ABC): uuid: Field(default_factory=lambda: uuid1().hex) name: str labels: list[str] transaction_from: datetime @abstractmethod async def save(self, driver: AsyncDriver): ... class EpisodicNode(Node): source: str # source type source_description: str # description of the data source content: str # raw episode data semantic_edges: list[str] # list of semantic edges referenced in this episode valid_from: datetime = None # datetime of when the original document was created async def save(self, driver: AsyncDriver): result = await driver.execute_query( """ MERGE (n:Episodic {uuid: $uuid}) SET n = {uuid: $uuid, name: $name, source_description: $source_description, content: $content, semantic_edges: $semantic_edges, transaction_from: $transaction_from, valid_from: $valid_from} RETURN n.uuid AS uuid""", uuid=self.uuid, name=self.name, source_description=self.source_description, content=self.content, semantic_edges=self.semantic_edges, transaction_from=self.transaction_from, valid_from=self.valid_from, _database="neo4j", ) logger.info(f"Saved Node to neo4j: {self.uuid}") print(self.uuid) return result class SemanticNode(Node): summary: str # regional summary of surrounding edges async def refresh_summary(self, driver: AsyncDriver, llm_client: OpenAI): ... async def save(self, driver: AsyncDriver): result = await driver.execute_query( """ MERGE (n:Semantic {uuid: $uuid}) SET n = {uuid: $uuid, name: $name, summary: $summary, transaction_from: $transaction_from} RETURN n.uuid AS uuid""", uuid=self.uuid, name=self.name, summary=self.summary, transaction_from=self.transaction_from, ) logger.info(f"Saved Node to neo4j: {self.uuid}") return result