James BruntonandGitHub
f9575c06fb
# Description of Changes Add Java orchestration layer which can connect and go back and forth with the AI engine to get results for the user. It's expected that the AI engine will not be publicly available and this Java layer will always be in front of it, to manage sessions and auth etc.
58 lines
1.4 KiB
Python
58 lines
1.4 KiB
Python
from __future__ import annotations
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from typing import Annotated, Literal
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from pydantic import Field
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from stirling.models import ApiModel
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from .agent_specs import AgentSpecStep
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from .common import ConversationMessage, StepKind, WorkflowOutcome
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from .pdf_edit import EditCannotDoResponse, EditClarificationRequest
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class AgentDraftStep(ApiModel):
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kind: Literal[StepKind.TOOL, StepKind.AI_TOOL]
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title: str
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description: str
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class AgentDraft(ApiModel):
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name: str
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description: str
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objective: str
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steps: list[AgentSpecStep] = Field(default_factory=list)
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class AgentDraftRequest(ApiModel):
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user_message: str
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conversation_history: list[ConversationMessage] = Field(default_factory=list)
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class AgentDraftResponse(ApiModel):
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outcome: Literal[WorkflowOutcome.DRAFT] = WorkflowOutcome.DRAFT
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draft: AgentDraft
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class AgentRevisionRequest(ApiModel):
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user_message: str
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conversation_history: list[ConversationMessage] = Field(default_factory=list)
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current_draft: AgentDraft
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class AgentRevisionResponse(ApiModel):
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outcome: Literal[WorkflowOutcome.DRAFT] = WorkflowOutcome.DRAFT
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draft: AgentDraft
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AgentDraftWorkflowResponse = Annotated[
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AgentDraftResponse | EditClarificationRequest | EditCannotDoResponse,
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Field(discriminator="outcome"),
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]
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AgentRevisionWorkflowResponse = Annotated[
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AgentRevisionResponse | EditClarificationRequest | EditCannotDoResponse,
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Field(discriminator="outcome"),
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]
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