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