059ad8162e
- Introduce new database models for conversation sessions, messages, and artifacts to support conversation history tracking. - Implement API routes for listing conversations and retrieving detailed conversation data, enhancing user interaction with historical records. - Add a conversation recorder service to persist conversation messages in real-time without disrupting ongoing calls. - Update the frontend to display conversation history, including filtering and sorting options, improving user experience. - Enhance the pipeline to integrate conversation history recording seamlessly during interactions.
237 lines
7.1 KiB
Python
237 lines
7.1 KiB
Python
"""面向前端的请求/响应 DTO。与 DB 模型解耦,**响应里的 key 一律打码**。
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模型资源 DTO 字段对齐前端 ComponentsModelsPage 的 ModelResource:
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JSON 用 camelCase(modelId/interfaceType/apiUrl/apiKey),Python 内部用 snake_case,
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靠 Pydantic alias 自动互转。FastAPI 响应默认 by_alias=True,所以出参也是 camelCase。
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"""
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from __future__ import annotations
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from datetime import datetime
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from typing import Annotated, Any, Literal, Union
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from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
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from pydantic.alias_generators import to_camel
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RuntimeMode = Literal["pipeline", "realtime"]
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ModelType = Literal["LLM", "ASR", "TTS", "Realtime", "Embedding", "Agent"]
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AssistantType = Literal["prompt", "workflow", "dify", "fastgpt", "opencode"]
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ToolType = Literal["end_call", "http"]
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ToolStatus = Literal["active", "archived", "draft"]
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ToolParameterType = Literal["string", "number", "integer", "boolean", "object", "array"]
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ToolParameterLocation = Literal["path", "query", "body", "header"]
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# 外部应用类型:其 config.apiKey 是该助手私有密钥,读时打码 / 写时哨兵
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EXTERNAL_TYPES = {"dify", "fastgpt", "opencode"}
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# 支持 realtime(语音到语音)的类型;外部托管大脑只能走 cascade。
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# 与 services.brains 各 BrainSpec.supported_runtime_modes 对齐(此处独立声明,
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# 避免 HTTP schema 层为做校验而引入 pipecat 重依赖)。
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REALTIME_CAPABLE_TYPES = {"prompt", "workflow"}
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class CamelModel(BaseModel):
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"""JSON camelCase ↔ Python snake_case。protected_namespaces 关掉以允许 model_id。"""
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model_config = ConfigDict(
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alias_generator=to_camel,
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populate_by_name=True,
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protected_namespaces=(),
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)
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# 各 type 允许的瘦字段(其余字段写入时清零,防止跨类型脏数据)
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ALLOWED_FIELDS: dict[str, set[str]] = {
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"prompt": {"prompt"},
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"workflow": {"graph"},
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"dify": {"api_url", "api_key"},
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"fastgpt": {"app_id", "api_url", "api_key"},
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"opencode": {"prompt", "api_url", "api_key"},
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}
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# ---------- 助手(单表 STI:瘦类型真列 + workflow 图 JSON 列) ----------
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class AssistantUpsert(CamelModel):
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name: str
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type: AssistantType = "prompt"
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runtime_mode: RuntimeMode = "pipeline"
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greeting: str = ""
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enable_interrupt: bool = True
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vision_enabled: bool = False
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vision_model_resource_id: str | None = None
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model_resource_ids: dict[ModelType, str] = Field(default_factory=dict)
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knowledge_base_id: str | None = None
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tool_ids: list[str] = Field(default_factory=list)
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# 瘦类型专属(真列);按 type 取用,无关字段写入时清零
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prompt: str = ""
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api_url: str = ""
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api_key: str = "" # 写时:占位符/空 → 保留旧(哨兵)
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app_id: str = ""
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# workflow 专属:图
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graph: dict[str, Any] = Field(default_factory=dict)
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@model_validator(mode="after")
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def _strip_irrelevant_fields(self):
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allowed = ALLOWED_FIELDS[self.type]
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for field in ("prompt", "api_url", "api_key", "app_id"):
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if field not in allowed:
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setattr(self, field, "")
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if "graph" not in allowed:
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self.graph = {}
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if self.type != "prompt":
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self.tool_ids = []
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# 外部托管大脑只能 cascade,拦住不兼容的 realtime
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if self.runtime_mode == "realtime" and self.type not in REALTIME_CAPABLE_TYPES:
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raise ValueError(f"类型 {self.type} 不支持 realtime 运行模式")
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return self
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class AssistantOut(AssistantUpsert):
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id: str
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updated_at: str | None = None
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# ---------- 可复用工具 ----------
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class ToolParameter(CamelModel):
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name: str
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type: ToolParameterType = "string"
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location: ToolParameterLocation = "body"
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description: str = ""
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required: bool = True
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class EndCallToolConfig(CamelModel):
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message_type: Literal["none", "custom"] = "none"
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custom_message: str = ""
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capture_reason: bool = True
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class HttpToolConfig(CamelModel):
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method: Literal["GET", "POST", "PUT", "PATCH", "DELETE"] = "GET"
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url: str
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timeout_seconds: int = Field(default=15, ge=1, le=120)
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headers: dict[str, str] = Field(default_factory=dict)
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parameters: list[ToolParameter] = Field(default_factory=list)
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body: dict[str, Any] = Field(default_factory=dict)
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@field_validator("url")
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@classmethod
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def validate_url(cls, value: str) -> str:
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if not value.startswith(("http://", "https://")):
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raise ValueError("HTTP 工具 URL 必须使用 http:// 或 https://")
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return value
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class EndCallToolDefinition(CamelModel):
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schema_version: int = 1
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type: Literal["end_call"] = "end_call"
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config: EndCallToolConfig = Field(default_factory=EndCallToolConfig)
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class HttpToolDefinition(CamelModel):
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schema_version: int = 1
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type: Literal["http"] = "http"
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config: HttpToolConfig
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ToolDefinition = Annotated[
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Union[EndCallToolDefinition, HttpToolDefinition], Field(discriminator="type")
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]
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class ToolUpsert(CamelModel):
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name: str = Field(min_length=1, max_length=128)
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function_name: str = Field(pattern=r"^[a-z][a-z0-9_]{0,63}$")
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description: str = Field(default="", max_length=2048)
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definition: ToolDefinition
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secrets: dict[str, Any] = Field(default_factory=dict)
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status: ToolStatus = "active"
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class ToolOut(ToolUpsert):
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id: str
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type: ToolType
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updated_at: str | None = None
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# ---------- 知识库 ----------
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class KnowledgeBaseUpsert(CamelModel):
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name: str
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description: str = ""
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embedding_model_resource_id: str | None = None
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class KnowledgeBaseOut(KnowledgeBaseUpsert):
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id: str
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status: str = "active"
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updated_at: str | None = None
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# ---------- 接口定义驱动的统一模型资源 ----------
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class InterfaceDefinitionOut(CamelModel):
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interface_type: str
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name: str
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capability: ModelType
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field_schema: dict[str, Any]
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enabled: bool
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version: int
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class ModelResourceUpsert(CamelModel):
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name: str
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interface_type: str
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values: dict[str, Any] = Field(default_factory=dict)
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secrets: dict[str, Any] = Field(default_factory=dict)
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support_image_input: bool = False
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enabled: bool = True
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is_default: bool = False
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class ModelResourceOut(ModelResourceUpsert):
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id: str
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capability: ModelType
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updated_at: str | None = None
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class ModelResourceTestResult(CamelModel):
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ok: bool
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latency_ms: int | None = None
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message: str
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detail: str = ""
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# ---------- 对话历史 ----------
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class ConversationMessageOut(CamelModel):
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id: str
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sequence: int
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role: Literal["user", "assistant"]
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content_type: str
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content: str
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occurred_at: datetime
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extra: dict[str, Any] = Field(default_factory=dict)
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class ConversationOut(CamelModel):
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id: str
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assistant_id: str | None
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assistant_name: str
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channel: str
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runtime_mode: str
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status: str
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message_count: int
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started_at: datetime
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ended_at: datetime | None
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class ConversationDetailOut(ConversationOut):
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messages: list[ConversationMessageOut] = Field(default_factory=list)
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class ConversationListOut(CamelModel):
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items: list[ConversationOut]
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total: int
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page: int
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page_size: int
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