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- Introduce BaseAsTokenCounter and EstimatedAsTokenCounter for token estimation - Add AsMsgStat and AsBlockStat schema for message statistics tracking - Implement FileIO class with read/write/append/edit operations - Create file utility functions for safe async file reading and truncation - Add MemorySearch component for semantic search in memory files - Register new component types in ComponentEnum and update imports - Add constants for default host, port, and truncation limits - Create BaseService abstract base class for service implementations - Implement BaseStep with component accessors and lifecycle management - Add proper __all__ exports for all new modules and components
29 lines
1.1 KiB
Python
29 lines
1.1 KiB
Python
"""Base node schema module.
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This module defines the BaseNode model, which serves as the foundational
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data structure for nodes in the knowledge graph or document processing pipeline.
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"""
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from uuid import uuid4
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from pydantic import BaseModel, Field
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class BaseNode(BaseModel):
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"""Base node model for graph and document structures.
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This model represents a single node in the knowledge graph or
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a chunk in the document processing pipeline. It contains text content,
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optional embeddings, and associated metadata.
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Attributes:
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id: Unique identifier for the node, auto-generated if not provided.
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text: Text content of the node.
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embedding: Optional vector embedding of the text content.
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metadata: Additional metadata associated with the node.
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"""
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id: str = Field(default_factory=lambda: uuid4().hex, description="Unique node identifier")
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text: str = Field(default="", description="Text content of the node")
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embedding: list[float] | None = Field(default=None, description="Vector embedding of text")
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metadata: dict = Field(default_factory=dict, description="Additional metadata")
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