mirror of
https://github.com/agentscope-ai/ReMe.git
synced 2026-09-23 00:43:18 +00:00
5b801c0d3e
* refactor(file_io): update file I/O operations and truncation logic * refactor(memory): update file-based memory compaction logic
144 lines
4.6 KiB
Python
144 lines
4.6 KiB
Python
"""Configuration schemas for service components using Pydantic models."""
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import os
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from pydantic import BaseModel, Field, ConfigDict
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from .tool_call import ToolCall
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class MCPConfig(BaseModel):
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"""Configuration for Model Context Protocol transport and network settings."""
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model_config = ConfigDict(extra="allow")
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transport: str = Field(default="stdio")
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host: str = Field(default="0.0.0.0")
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port: int = Field(default=8001)
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class HttpConfig(BaseModel):
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"""Configuration for the HTTP server interface and connection lifecycle."""
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model_config = ConfigDict(extra="allow")
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host: str = Field(default="0.0.0.0")
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port: int = Field(default=8001)
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timeout_keep_alive: int = Field(default=3600)
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limit_concurrency: int = Field(default=1000)
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class CmdConfig(BaseModel):
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"""Configuration for command-line flow execution parameters."""
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model_config = ConfigDict(extra="allow")
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flow: str = Field(default="")
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class OpConfig(BaseModel):
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"""Configuration for op settings and parameters."""
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model_config = ConfigDict(extra="allow")
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prompt_dict: dict[str, str] = Field(default_factory=dict)
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params: dict = Field(default_factory=dict)
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class FlowConfig(ToolCall):
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"""Configuration for workflow execution, caching, and error handling."""
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model_config = ConfigDict(extra="allow")
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flow_content: str = Field(default="")
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stream: bool = Field(default=False)
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raise_exception: bool = Field(default=True)
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enable_cache: bool = Field(default=False)
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cache_path: str = Field(default="cache/flow")
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cache_expire_hours: float = Field(default=0.1)
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class BasicConfig(BaseModel):
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"""Configuration for basic service settings and parameters."""
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model_config = ConfigDict(extra="allow")
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backend: str = Field(default="")
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class ModelConfig(BasicConfig):
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"""Configuration for model-based services with backend and model name."""
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model_name: str = Field(default="")
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class LLMConfig(ModelConfig):
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"""Configuration for Large Language Model backend and model identification."""
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class EmbeddingModelConfig(ModelConfig):
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"""Configuration for embedding model backends and identity."""
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class TokenCounterConfig(ModelConfig):
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"""Configuration for token counting services and model mapping."""
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class StoreConfig(BasicConfig):
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"""Configuration for storage services with embedding model support."""
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embedding_model: str = Field(default="default")
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class VectorStoreConfig(StoreConfig):
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"""Configuration for vector database storage and associated embeddings."""
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collection_name: str = Field(default="reme")
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class FileStoreConfig(StoreConfig):
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"""Configuration for file store database storage and associated embeddings."""
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store_name: str = Field(default="reme")
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class FileWatcherConfig(BasicConfig):
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"""Configuration for file watcher service."""
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file_store: str = Field(default="")
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watch_paths: list[str] = Field(default_factory=list)
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class ServiceConfig(BasicConfig):
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"""Root configuration schema aggregating all service-level settings and components."""
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app_name: str = Field(default=os.getenv("APP_NAME", "ReMe"))
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working_dir: str = Field(default=".reme")
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enable_logo: bool = Field(default=True)
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language: str = Field(default="")
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thread_pool_max_workers: int = Field(
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default=16,
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description="Number of thread pool workers. Set to -1 to disable thread pool.",
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)
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ray_max_workers: int = Field(default=-1)
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log_to_console: bool = Field(default=True)
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disabled_flows: list[str] = Field(default_factory=list)
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enabled_flows: list[str] = Field(default_factory=list)
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mcp_servers: dict[str, dict] = Field(default_factory=dict)
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mcp: MCPConfig = Field(default_factory=MCPConfig)
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http: HttpConfig = Field(default_factory=HttpConfig)
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cmd: CmdConfig = Field(default_factory=CmdConfig)
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ops: dict[str, OpConfig] = Field(default_factory=dict)
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flows: dict[str, FlowConfig] = Field(default_factory=dict)
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as_llms: dict[str, BasicConfig] = Field(default_factory=dict)
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as_llm_formatters: dict[str, BasicConfig] = Field(default_factory=dict)
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as_token_counters: dict[str, BasicConfig] = Field(default_factory=dict)
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llms: dict[str, LLMConfig] = Field(default_factory=dict)
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embedding_models: dict[str, EmbeddingModelConfig] = Field(default_factory=dict)
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vector_stores: dict[str, VectorStoreConfig] = Field(default_factory=dict)
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file_stores: dict[str, FileStoreConfig] = Field(default_factory=dict)
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token_counters: dict[str, TokenCounterConfig] = Field(default_factory=dict)
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file_watchers: dict[str, FileWatcherConfig] = Field(default_factory=dict)
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metadata: dict = Field(default_factory=dict)
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