agents.planning.enhanced_plan_execute_v5.planner.models¶

Planner Models - Custom Pydantic models for strategic planning.

This module defines the structured output models used by the planner agent for creating comprehensive, actionable task plans.

Classes¶

`PlanningContext`	Context information for the planner agent.
`TaskPlan`	Comprehensive task plan with metadata and execution strategy.
`TaskStep`	Individual step in a task plan with rich metadata.

Module Contents¶

class agents.planning.enhanced_plan_execute_v5.planner.models.PlanningContext(/, **data)¶

Bases: pydantic.BaseModel

Context information for the planner agent.

Provides additional context that helps the planner create better, more targeted plans based on available resources and constraints.

Parameters:: data (Any)

available_tools¶: Tools that can be used during execution

time_constraints¶: Any time limitations to consider

complexity_level¶: Desired complexity level for the plan

domain_focus¶: Specific domain or area of focus

previous_attempts¶: Information about previous planning attempts

Examples

Research context:

context = PlanningContext(
    available_tools=["web_search", "calculator", "document_reader"],
    time_constraints="Complete within 1 hour",
    complexity_level="detailed",
    domain_focus="financial_analysis"
)

Simple task context:

context = PlanningContext(
    available_tools=["calculator"],
    complexity_level="simple",
    domain_focus="mathematics"
)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

class agents.planning.enhanced_plan_execute_v5.planner.models.TaskPlan(/, **data)¶

Bases: pydantic.BaseModel

Comprehensive task plan with metadata and execution strategy.

Represents a complete strategic plan for accomplishing a complex objective, including all steps, reasoning, and success criteria.

Parameters:: data (Any)

objective¶: The main goal we’re trying to achieve

steps¶: Ordered list of steps to execute

reasoning¶: Explanation of the planning approach

success_criteria¶: How we’ll know the objective is achieved

estimated_total_time¶: Total estimated time for all steps

plan_type¶: Type of planning strategy used

risk_factors¶: Potential risks and mitigation strategies

Examples

Research plan:

plan = TaskPlan(
    objective="Research Tesla's Q4 2024 financial performance",
    steps=[search_step, analysis_step, summary_step],
    reasoning="Sequential approach: gather data, analyze, summarize",
    success_criteria="Complete financial overview with key metrics",
    plan_type="sequential_research"
)

Complex analysis plan:

plan = TaskPlan(
    objective="Compare renewable energy adoption across countries",
    steps=[data_steps, comparison_steps, visualization_step],
    reasoning="Parallel data gathering followed by comparative analysis",
    success_criteria="Comprehensive comparison with visual insights",
    plan_type="comparative_analysis",
    risk_factors=["Data availability", "Currency conversion accuracy"]
)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

class agents.planning.enhanced_plan_execute_v5.planner.models.TaskStep(/, **data)¶

Bases: pydantic.BaseModel

Individual step in a task plan with rich metadata.

Represents a single actionable step within a larger plan, including all the information needed for successful execution.

Parameters:: data (Any)

step_id¶: Unique identifier for tracking this step

description¶: Clear, actionable description of what to do

expected_outcome¶: What result this step should produce

tools_needed¶: Tools required for execution

priority¶: Execution priority level

estimated_time¶: Estimated completion time

dependencies¶: Steps that must complete before this one

Examples

Basic step:

step = TaskStep(
    step_id="step_1",
    description="Search for current stock price of AAPL",
    expected_outcome="Current AAPL stock price in USD",
    tools_needed=["web_search"],
    priority="high"
)

Step with dependencies:

step = TaskStep(
    step_id="step_2",
    description="Calculate percentage change from yesterday",
    expected_outcome="Percentage change calculation",
    tools_needed=["calculator"],
    dependencies=["step_1"],
    priority="medium"
)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.