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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
80 lines
3.4 KiB
Python
80 lines
3.4 KiB
Python
"""Application configuration schema module.
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This module defines the configuration models for the ReMe CLI application,
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including application-level settings, service configuration, and job definitions.
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"""
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import os
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from pydantic import BaseModel, ConfigDict, Field
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from ..enumeration import ComponentEnum
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class ComponentConfig(BaseModel):
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"""Base configuration for a component.
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This serves as the base class for all component configurations,
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allowing extra fields to be defined dynamically.
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Attributes:
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backend: The backend implementation class name for this component.
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"""
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model_config = ConfigDict(extra="allow")
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backend: str = Field(default="", description="Backend implementation class name")
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class JobConfig(ComponentConfig):
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"""Configuration for a job definition.
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A job represents a sequence of steps that can be executed
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as part of the application workflow.
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Attributes:
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name: Unique identifier name for the job.
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description: Human-readable description of what the job does.
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parameters: Job-level parameters passed to all steps.
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steps: Ordered list of step configurations to execute.
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"""
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name: str = Field(default="", description="Unique job identifier")
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description: str = Field(default="", description="Human-readable job description")
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parameters: dict = Field(default_factory=dict, description="Job-level parameters")
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steps: list[ComponentConfig] = Field(default_factory=list, description="Ordered list of step configs")
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class ApplicationConfig(BaseModel):
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"""Root configuration for the ReMe CLI application.
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This model contains all configuration settings needed to initialize
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and run the application, including service endpoints, job definitions,
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and component registry.
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Attributes:
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app_name: Display name of the application.
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working_dir: Working directory for runtime files and logs.
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enable_logo: Whether to display the ASCII logo on startup.
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language: Default language for LLM interactions.
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log_to_console: Whether to output logs to console.
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log_to_file: Whether to write logs to a file.
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mcp_servers: MCP server configurations indexed by name.
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service: Service endpoint configuration.
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jobs: List of job definitions.
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components: Component registry indexed by component type and name.
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"""
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app_name: str = Field(default=os.getenv("APP_NAME", "ReMe"), description="Application display name")
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working_dir: str = Field(default=".reme", description="Working directory for runtime files")
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enable_logo: bool = Field(default=False, description="Whether to show ASCII logo on startup")
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language: str = Field(default="", description="Default language for LLM interactions")
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log_to_console: bool = Field(default=True, description="Whether to log to console")
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log_to_file: bool = Field(default=True, description="Whether to log to file")
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mcp_servers: dict[str, dict] = Field(default_factory=dict, description="MCP server configurations")
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service: ComponentConfig = Field(default_factory=ComponentConfig, description="Service endpoint config")
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jobs: list[JobConfig] = Field(default_factory=list, description="Job definitions")
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components: dict[ComponentEnum, dict[str, ComponentConfig]] = Field(
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default_factory=dict,
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description="Component registry by type",
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)
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