mirror of
https://github.com/agentscope-ai/ReMe.git
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cee2c3e338
* feat(config): add jsonl support and update LLM integration tests - Added jsonl extension to supported extensions in chunked backend - Refactored LLM integration tests to use async functions instead of nested runs - Created helper functions _run_basic_chat, _run_with_tool, _run_structured_output, _run_structured_output_enum - Implemented _run_all function to execute all test scenarios sequentially - Updated main execution block to use asyncio.run with consolidated test runner - Maintained all original test functionality while improving code structure * feat(config): add dialog directory configuration and reorganize vault structure - Add new dialog_dir field for dialog memory storage - Reorder directory initialization sequence in application setup - Simplify vault_dir description in configuration schema - Update thread_pool_max_workers description to be more concise - Move resource_dir definition earlier in the configuration schema - Remove redundant text from digest_dir description * docs(reme): update design documentation with layered memory architecture - Replace quick test section with comprehensive layered memory structure - Add detailed explanation of three-tier memory organization (resource, daily, digest) - Document Obsidian-compatible Markdown format with YAML front matter - Describe four types of wikilink syntax and semantic linking features - Explain AST-aware semantic chunking for document parsing - Detail self-evolving system with auto-resource, auto-memory, and auto-dream - Document directory structure and lifecycle characteristics - Add comprehensive table showing content nature, triggers, and examples - Include semantic link extraction and knowledge graph formation processes - Describe automated indexing and relationship building workflows * docs(reme): update design documentation with simplified structure and clearer explanations - Simplified directory structure overview with cleaner formatting - Updated memory layering explanation with more concise descriptions - Improved table layouts for better readability - Clarified auto-resource, auto-memory, and auto-dream processes - Streamlined indexing and search mechanism descriptions - Enhanced component system documentation with clearer backend options - Refined job list with more precise functional descriptions - Modernized layout diagrams and process flows - Consolidated repetitive content while maintaining comprehensive coverage * docs(reme): add application scenario documentation for financial industry use case - Document comprehensive example of ReMe usage in新能源 industry research - Detail the week-long process of automatic knowledge graph construction - Explain the auto-memory and auto-dream pipeline with concrete examples - Describe the extract and integrate phases for creating wiki nodes - Illustrate cross-file linking through relates_to and derived_from predicates - Show progressive graph growth from daily sessions to complete ecosystem - Demonstrate hybrid retrieval with vector and keyword search capabilities - Provide detailed directory structure and file organization patterns - Explain the three-phase workflow: ingestion, processing, and retrieval - Document the financial analyst persona and their information management needs * style(config): fix spacing in thread_pool_max_workers field definition - Corrected spacing around description parameter in Field definition - Simplified multi-line assertion to single line in LLM integration test
48 lines
2.6 KiB
Python
48 lines
2.6 KiB
Python
"""Application configuration models."""
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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 config for a component; extra fields allowed for backend-specific options."""
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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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"""Config for a job — an ordered sequence of step components. Keyed by name in ApplicationConfig.jobs."""
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description: str = Field(default="", description="Human-readable 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 step configs")
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enable_serve: bool = Field(default=True, description="Whether to expose this job through the service layer")
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class ApplicationConfig(BaseModel):
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"""Root config for the ReMe application."""
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app_name: str = Field(default=os.getenv("APP_NAME", "ReMe"), description="Application display name")
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vault_dir: str = Field(default=".reme", description="Vault root directory for runtime files")
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metadata_dir: str = Field(default="reme_metadata", description="Subdirectory for ReMe persistent state")
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resource_dir: str = Field(default="resource", description="Subdirectory for external assets")
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dialog_dir: str = Field(default="dialog", description="Subdirectory for dialog memory")
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daily_dir: str = Field(default="daily", description="Subdirectory for daily memory")
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digest_dir: str = Field(default="digest", description="Subdirectory for digest memory")
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enable_logo: bool = Field(default=True, description="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="Log to console")
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log_to_file: bool = Field(default=True, description="Log to file")
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mcp_servers: dict[str, dict] = Field(default_factory=dict, description="MCP server configs by name")
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service: ComponentConfig = Field(default_factory=ComponentConfig, description="Service endpoint config")
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jobs: dict[str, JobConfig] = Field(default_factory=dict, description="Job definitions keyed by job name")
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thread_pool_max_workers: int = Field(default=0, description="Max worker threads; 0 to disable")
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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 keyed by type then name",
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)
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