Refactor Workflow and Chat Architecture (#68)
* refactor: overhaul workflow and chat architecture - Separate Chat and Workflow API endpoints and database models - Use JSONB to store workflow execution context in Postgres - Convert workflow engine to use pydantic-ai execution graphs inside a Ray task - Update frontend React components to support standalone workflow creation - Remove obsolete and broken workflow runner tests Co-authored-by: zhaoxi826 <198742034+zhaoxi826@users.noreply.github.com> * refactor: overhaul workflow and chat architecture - Separate Chat and Workflow API endpoints and database models - Use JSONB to store workflow execution context in Postgres - Convert workflow engine to use pydantic-ai execution graphs inside a Ray task - Update frontend React components to support standalone workflow creation - Remove obsolete and broken workflow runner tests Co-authored-by: zhaoxi826 <198742034+zhaoxi826@users.noreply.github.com> * refactor: overhaul workflow and chat architecture - Separate Chat and Workflow API endpoints and database models - Use JSONB to store workflow execution context in Postgres - Convert workflow engine to use pydantic-ai execution graphs inside a Ray task - Update frontend React components to support standalone workflow creation - Move workflow_engine inside workflow package to keep core root clean - Remove obsolete and broken workflow runner tests Co-authored-by: zhaoxi826 <198742034+zhaoxi826@users.noreply.github.com> --------- Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com> Co-authored-by: zhaoxi826 <198742034+zhaoxi826@users.noreply.github.com>
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@@ -15,5 +15,21 @@
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from kilostar.core.postgres_database.model.user import User
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from kilostar.core.postgres_database.model.provider import Provider
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from kilostar.core.postgres_database.model.individual import WorkerIndividual
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from kilostar.core.postgres_database.model.workflow import (
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Workflow,
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WorkflowContextModel,
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)
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from kilostar.core.postgres_database.model.chat_history import (
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ChatHistoryRegister,
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ChatHistoryMessage,
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)
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__all__ = ["User", "Provider", "WorkerIndividual"]
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__all__ = [
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"User",
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"Provider",
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"WorkerIndividual",
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"Workflow",
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"WorkflowContextModel",
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"ChatHistoryRegister",
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"ChatHistoryMessage",
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]
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@@ -15,5 +15,6 @@
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from sqlalchemy.ext.asyncio import AsyncAttrs
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from sqlalchemy.orm import DeclarativeBase
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class BaseDataModel(DeclarativeBase, AsyncAttrs):
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pass
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pass
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@@ -11,19 +11,55 @@
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import Literal
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from sqlalchemy import String, DateTime, func
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from sqlalchemy.orm import Mapped, mapped_column
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from .base import BaseDataModel
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from sqlalchemy.orm import Mapped
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class ChatHistoryMessage(BaseDataModel):
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__tablename__ = "chat_history_massage"
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message_id: Mapped[str]
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message: Mapped[str]
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message_owner: Literal["user","regulatory_node"]
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class ChatHistoryRegister(BaseDataModel):
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__tablename__ = "chat_history_register"
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chat_id: Mapped[str]
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user_id: Mapped[str]
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"""
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一个特定的聊天会话记录注册表。
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类似于多会话的一个 Thread/Session。
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"""
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__tablename__ = "chat_history_register"
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chat_id: Mapped[str] = mapped_column(
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String(64), primary_key=True, description="聊天会话ID"
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)
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user_id: Mapped[str] = mapped_column(
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String(64), index=True, description="归属的用户ID"
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)
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title: Mapped[str] = mapped_column(
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String(255), default="新对话", description="对话标题"
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)
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created_at: Mapped[str] = mapped_column(
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DateTime(timezone=True), server_default=func.now()
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)
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updated_at: Mapped[str] = mapped_column(
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DateTime(timezone=True), server_default=func.now(), onupdate=func.now()
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)
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class ChatHistoryMessage(BaseDataModel):
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"""
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特定会话中的每一条具体消息记录。
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"""
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__tablename__ = "chat_history_message"
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message_id: Mapped[str] = mapped_column(
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String(64), primary_key=True, description="消息ID"
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)
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chat_id: Mapped[str] = mapped_column(
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String(64), index=True, description="所属会话ID"
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)
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message: Mapped[str] = mapped_column(String, description="消息体内容")
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message_owner: Mapped[str] = mapped_column(
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String(50),
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description="消息发送方，例如 'user', 'regulatory_node', 'consciousness_node' 等",
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)
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created_at: Mapped[str] = mapped_column(
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DateTime(timezone=True), server_default=func.now()
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)
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@@ -44,10 +44,7 @@ class BaseIndividualModel(BaseDataModel):
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agent_type: Mapped[str] = mapped_column(String(32))
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__mapper_args__ = {
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"polymorphic_on": "agent_type",
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"polymorphic_identity": "base"
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}
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__mapper_args__ = {"polymorphic_on": "agent_type", "polymorphic_identity": "base"}
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# ==========================================
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@@ -57,8 +54,7 @@ class SpecialistIndividualModel(BaseIndividualModel):
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__tablename__ = "specialist_individual"
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agent_id: Mapped[str] = mapped_column(
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ForeignKey("base_individual.agent_id", ondelete="CASCADE"),
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primary_key=True
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ForeignKey("base_individual.agent_id", ondelete="CASCADE"), primary_key=True
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)
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bound_skill: Mapped[Optional[Dict[str, Any]]] = mapped_column(JSONB)
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workspace: Mapped[Optional[List[str]]] = mapped_column(JSONB)
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@@ -70,12 +66,12 @@ class SpecialistIndividualModel(BaseIndividualModel):
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sub_ordinary_agents: Mapped[List["OrdinaryIndividualModel"]] = relationship(
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back_populates="manager",
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cascade="all, delete-orphan",
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foreign_keys="[OrdinaryIndividualModel.manager_id]"
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foreign_keys="[OrdinaryIndividualModel.manager_id]",
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)
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sub_special_agents: Mapped[List["SpecialIndividualModel"]] = relationship(
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back_populates="manager",
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cascade="all, delete-orphan",
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foreign_keys="[SpecialIndividualModel.manager_id]"
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foreign_keys="[SpecialIndividualModel.manager_id]",
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)
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__mapper_args__ = {
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@@ -90,8 +86,7 @@ class OrdinaryIndividualModel(BaseIndividualModel):
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__tablename__ = "ordinary_individual"
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agent_id: Mapped[str] = mapped_column(
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ForeignKey("base_individual.agent_id", ondelete="CASCADE"),
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primary_key=True
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ForeignKey("base_individual.agent_id", ondelete="CASCADE"), primary_key=True
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)
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finetuned_from: Mapped[Optional[str]] = mapped_column(String(100))
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tools: Mapped[Optional[List[str]]] = mapped_column(
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@@ -106,7 +101,7 @@ class OrdinaryIndividualModel(BaseIndividualModel):
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# 逻辑关联：指向上级专家
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manager: Mapped[Optional["SpecialistIndividualModel"]] = relationship(
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back_populates="sub_ordinary_agents",
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foreign_keys=[manager_id] # 显式指定使用 manager_id 解析关系
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foreign_keys=[manager_id], # 显式指定使用 manager_id 解析关系
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)
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__mapper_args__ = {
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@@ -121,12 +116,10 @@ class SpecialIndividualModel(BaseIndividualModel):
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__tablename__ = "special_individual"
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agent_id: Mapped[str] = mapped_column(
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ForeignKey("base_individual.agent_id", ondelete="CASCADE"),
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primary_key=True
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ForeignKey("base_individual.agent_id", ondelete="CASCADE"), primary_key=True
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)
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modality_type: Mapped[ModalityType] = mapped_column(
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default=ModalityType.MULTIMODAL,
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server_default=text("'multimodal'")
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default=ModalityType.MULTIMODAL, server_default=text("'multimodal'")
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)
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multimodal_config: Mapped[Optional[Dict[str, Any]]] = mapped_column(JSONB)
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@@ -137,10 +130,9 @@ class SpecialIndividualModel(BaseIndividualModel):
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# 【修复2】：修正 back_populates 指向正确的变量名
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manager: Mapped[Optional["SpecialistIndividualModel"]] = relationship(
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back_populates="sub_special_agents",
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foreign_keys=[manager_id]
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back_populates="sub_special_agents", foreign_keys=[manager_id]
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)
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__mapper_args__ = {
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"polymorphic_identity": "special",
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}
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}
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@@ -24,6 +24,7 @@ class ProviderModel(BaseDataModel):
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Provider 物理模型。
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作为模型/服务提供商适配器，标准化不同供应商（OpenAI, Anthropic 等）的配置。
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"""
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__tablename__ = "provider"
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provider_id: Mapped[str] = mapped_column(String(64), primary_key=True)
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provider_title: Mapped[str] = mapped_column(String(100), index=True, nullable=False)
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@@ -31,14 +32,12 @@ class ProviderModel(BaseDataModel):
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provider_url: Mapped[Optional[str]] = mapped_column(Text)
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provider_apikey: Mapped[Optional[str]] = mapped_column(Text)
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provider_models: Mapped[List[str]] = mapped_column(
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JSONB,
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default=list,
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server_default=text("'[]'::jsonb")
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JSONB, default=list, server_default=text("'[]'::jsonb")
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)
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provider_owner: Mapped[str] = mapped_column(String(64), index=True)
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is_active: Mapped[bool] = mapped_column(
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Boolean,
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default=True,
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server_default=text("true"),
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comment="该服务商节点是否在线/启用"
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comment="该服务商节点是否在线/启用",
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)
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@@ -13,10 +13,12 @@
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# limitations under the License.
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from typing import List, Optional
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from sqlalchemy import String, Text
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from sqlalchemy.dialects.postgresql import JSONB # 针对 Postgres 优化，支持索引和高性能解析
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from sqlalchemy import String
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from sqlalchemy.dialects.postgresql import (
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JSONB,
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) # 针对 Postgres 优化，支持索引和高性能解析
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from sqlalchemy.orm import Mapped, mapped_column
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from .base import BaseDataModel
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from .base import BaseDataModel
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class SystemNodeConfigModel(BaseDataModel):
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@@ -24,12 +26,11 @@ class SystemNodeConfigModel(BaseDataModel):
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SystemNodeConfig 物理模型。
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作为 kilostar 架构中的独立处理单元，负责存储 LLM 节点的执行策略与工具配置。
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"""
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__tablename__ = "system_node_config"
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node_name: Mapped[str] = mapped_column(String(100), primary_key=True)
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provider_title: Mapped[str] = mapped_column(String(50), nullable=False)
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model_id: Mapped[str] = mapped_column(String(100), nullable=False)
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tools: Mapped[Optional[List[str]]] = mapped_column(
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JSONB,
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default=list,
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comment="节点可调用的工具标识列表"
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JSONB, default=list, comment="节点可调用的工具标识列表"
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)
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@@ -25,6 +25,7 @@ class UserAuthority(IntEnum):
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"""
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权限枚举类
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"""
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SUPER_ADMINISTRATOR = 100
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ADMINISTRATOR = 50
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USER = 20
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@@ -36,12 +37,11 @@ class User(BaseDataModel):
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"""
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数据库user表模型
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"""
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__tablename__ = "user"
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user_id: Mapped[str] = mapped_column(String(64), primary_key=True)
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user_name: Mapped[str] = mapped_column(String(100), index=True, nullable=False)
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hashed_password: Mapped[str] = mapped_column(String(255), nullable=False)
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user_authority: Mapped[UserAuthority] = mapped_column(
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Integer,
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default=UserAuthority.USER,
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server_default=text("20")
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Integer, default=UserAuthority.USER, server_default=text("20")
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)
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@@ -12,12 +12,70 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from sqlmodel import SQLModel, Field
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from sqlalchemy import String, DateTime, func
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from sqlalchemy.orm import Mapped, mapped_column
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from sqlalchemy.dialects.postgresql import JSONB
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from .base import BaseDataModel
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class EventRecord(SQLModel, table=True):
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trace_id: str = Field(
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primary_key=True, description="The unique trace ID of the kilostarEvent"
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class Workflow(BaseDataModel):
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__tablename__ = "workflow"
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trace_id: Mapped[str] = mapped_column(
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String(64), primary_key=True, description="工作流唯一ID (Trace ID)"
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)
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user_id: Mapped[str] = mapped_column(
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String(64), index=True, description="创建该工作流的用户ID"
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)
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title: Mapped[str] = mapped_column(String(255), description="工作流标题/简短描述")
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command: Mapped[str] = mapped_column(
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String, description="创建工作流的原始用户命令文本"
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)
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status: Mapped[str] = mapped_column(
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String(50),
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default="creating",
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description="工作流的总体状态 (例如: creating, running, pending, completed, failed等)",
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)
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version: Mapped[str] = mapped_column(
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String(50), default="v1.0", description="系统协议版本号"
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)
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created_at: Mapped[str] = mapped_column(
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DateTime(timezone=True), server_default=func.now()
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)
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updated_at: Mapped[str] = mapped_column(
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DateTime(timezone=True), server_default=func.now(), onupdate=func.now()
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)
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class WorkflowContextModel(BaseDataModel):
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__tablename__ = "workflow_context"
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trace_id: Mapped[str] = mapped_column(
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String(64), primary_key=True, description="对应的工作流 Trace ID"
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)
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workflow_status: Mapped[dict] = mapped_column(
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JSONB, default=dict, description="工作流状态变更历史"
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)
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blackboard: Mapped[dict] = mapped_column(
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JSONB, default=dict, description="大模型输出的存储区 (共享黑板)"
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)
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work_step_status: Mapped[dict] = mapped_column(
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JSONB, nullable=True, description="工作流运行步骤状态"
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)
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workflow_pointer: Mapped[int] = mapped_column(
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nullable=True, description="工作流指针，指向具体运行步骤位置"
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)
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workflow_log: Mapped[list] = mapped_column(
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JSONB, default=list, description="工作流运行日志"
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)
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work_link: Mapped[list] = mapped_column(
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JSONB,
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default=list,
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description="工作链(即 WorkflowStep 的定义列表，包含图结构和原子动作)",
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)
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created_at: Mapped[str] = mapped_column(
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DateTime(timezone=True), server_default=func.now()
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)
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updated_at: Mapped[str] = mapped_column(
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DateTime(timezone=True), server_default=func.now(), onupdate=func.now()
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)
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event_data_json: str = Field(description="The JSON serialized kilostarEvent data")
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