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81 lines
3.0 KiB
Python
81 lines
3.0 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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"""Pydantic models for structured planning output.
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These models define the JSON schema that the agent produces when in planning
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mode via `response_format`. The schema enables consistent rendering of
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clarification questions and approval requests in the console UI.
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"""
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from __future__ import annotations
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from enum import Enum
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from pydantic import BaseModel, Field
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class PlanningResponseType(str, Enum):
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"""Type of planning response from the agent."""
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CLARIFICATION = "clarification"
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"""The agent needs clarification and presents options for the user to choose from."""
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APPROVAL = "approval"
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"""The agent is seeking approval to proceed with execution."""
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class PlanningQuestion(BaseModel):
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"""A single question or item within a PlanningResponse.
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For clarification: contains the question text and optional choices.
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For approval: contains the plan summary for the user to approve.
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"""
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message: str = Field(
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description=(
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"For clarifications, this has the question that needs to be clarified "
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"with the user. For approvals, this would contain a summary of the "
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"execution plan that the user needs to approve."
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),
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)
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choices: list[str] | None = Field(
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default=None,
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description=(
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"For clarifications, this has a list of options that the user can "
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"choose from. null for approvals.\n\n"
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"Note: for clarifications, the user will always also be presented with "
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"a free form input option, so make sure that each choice provided here "
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"is a valid input for the next turn.\n"
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'E.g. if the question is "Which stock are you referring to?" then valid '
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'choices might be ["AAPL", "MSFT", "GOOG"], and the user could also type '
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"their own answer.\n"
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'Invalid choices would be ["Enter tickers directly", "Paste tickers"], '
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"since these conflict with the already existing freeform option, and "
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"don't directly provide valid inputs for the next turn."
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),
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)
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class PlanningResponse(BaseModel):
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"""Structured response from the agent while in planning mode.
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Used with structured output (`response_format`) to enable consistent
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rendering of clarification questions and approval requests.
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"""
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type: PlanningResponseType = Field(
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description=(
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"Use 'clarification' when you need clarification around the user "
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"request and you want to present the user with options to choose from. "
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"Use 'approval' when you are ready to start execution, but need "
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"approval to start executing."
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),
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)
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questions: list[PlanningQuestion] = Field(
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description=(
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"For clarifications, this has one or more questions to ask the user "
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"(each with choices). For approvals, this has exactly one item "
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"containing the plan summary for the user to approve."
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),
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)
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