prebuilt.startup.ideation.models¶

Startup idea models for the Haive framework.

This module provides comprehensive data models for brainstorming, researching, and evaluating startup ideas using AI agents. These models integrate with the pitch deck models to create a complete startup development pipeline.

The models support: - Idea generation and brainstorming - Market research and validation - Competitive analysis - Problem-solution fit assessment - Business model exploration - Risk and opportunity analysis

Classes¶

`BusinessModelCanvas`	Business model canvas for startup ideas.
`CompetitorAnalysis`	Analysis of a specific competitor.
`IdeaBrainstorm`	A brainstorming session for generating startup ideas.
`IdeaCategory`	Categories of startup ideas.
`IdeaGenerationRequest`	Request model for idea generation.
`IdeaGenerationResponse`	Response model for idea generation.
`IdeaMetrics`	Metrics for evaluating startup ideas.
`IdeaPortfolio`	Portfolio of startup ideas being developed.
`IdeaStage`	Stage of idea development.
`MarketResearch`	Market research data for a startup idea.
`MarketSize`	Market size categories.
`ProblemStatement`	Defines a problem that the startup idea aims to solve.
`RiskAssessment`	Risk assessment for a startup idea.
`RiskLevel`	Risk level assessment.
`SolutionConcept`	Defines a solution concept for a problem.
`StartupIdea`	Complete startup idea with all research and validation.
`ValidationMethod`	Methods for validating ideas.
`ValidationResult`	Results from idea validation activities.

Functions¶

`create_basic_idea`(name, problem, solution, category)	Create a basic startup idea from minimal information.
`create_problem_from_description`(description[, severity])	Create a problem statement from a simple description.

Module Contents¶

class prebuilt.startup.ideation.models.BusinessModelCanvas(/, **data)¶

Bases: pydantic.BaseModel

Business model canvas for startup ideas.

Based on the standard Business Model Canvas framework.

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.

Parameters:: data (Any)

classmethod validate_required_lists(v, info)¶: Ensure critical lists are not empty.

model_config¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class prebuilt.startup.ideation.models.CompetitorAnalysis(/, **data)¶

Bases: pydantic.BaseModel

Analysis of a specific competitor.

Detailed competitive intelligence for strategic planning.

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.

Parameters:: data (Any)

model_config¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class prebuilt.startup.ideation.models.IdeaBrainstorm(/, **data)¶

Bases: pydantic.BaseModel

A brainstorming session for generating startup ideas.

Tracks the ideation process and generated concepts.

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.

Parameters:: data (Any)

add_raw_idea(idea, agent_id=None)¶

Add a raw idea to the session.

Parameters:

idea (str)
agent_id (str | None)

Return type:

None

model_config¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class prebuilt.startup.ideation.models.IdeaCategory¶

Bases: str, enum.Enum

Categories of startup ideas.

Initialize self. See help(type(self)) for accurate signature.

class prebuilt.startup.ideation.models.IdeaGenerationRequest(/, **data)¶

Bases: pydantic.BaseModel

Request model for idea generation.

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.

Parameters:: data (Any)

class prebuilt.startup.ideation.models.IdeaGenerationResponse(/, **data)¶

Bases: pydantic.BaseModel

Response model for idea generation.

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.

Parameters:: data (Any)

class prebuilt.startup.ideation.models.IdeaMetrics(/, **data)¶

Bases: pydantic.BaseModel

Metrics for evaluating startup ideas.

Comprehensive scoring across multiple dimensions.

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.

Parameters:: data (Any)

calculate_scores()¶: Calculate overall scores.

model_config¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class prebuilt.startup.ideation.models.IdeaPortfolio(/, **data)¶

Bases: pydantic.BaseModel

Portfolio of startup ideas being developed.

Manages multiple ideas and tracks their progress.

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.

Parameters:: data (Any)

add_idea(idea)¶

Add an idea to the portfolio.

Parameters:: idea (StartupIdea)
Return type:: bool

get_ideas_by_stage(stage)¶

Get all ideas at a specific stage.

Parameters:: stage (IdeaStage)
Return type:: list[StartupIdea]

get_portfolio_summary()¶

Get summary statistics of the portfolio.

Return type:: dict[str, Any]

get_top_ideas(n=3)¶

Get top N ideas by score.

Parameters:: n (int)
Return type:: list[StartupIdea]

model_config¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class prebuilt.startup.ideation.models.IdeaStage¶

Bases: str, enum.Enum

Stage of idea development.

Initialize self. See help(type(self)) for accurate signature.

class prebuilt.startup.ideation.models.MarketResearch(/, **data)¶

Bases: pydantic.BaseModel

Market research data for a startup idea.

Contains comprehensive market analysis and research findings.

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.

Parameters:: data (Any)

validate_market_sizes()¶: Ensure market sizes are logical.

model_config¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class prebuilt.startup.ideation.models.MarketSize¶

Bases: str, enum.Enum

Market size categories.

Initialize self. See help(type(self)) for accurate signature.

class prebuilt.startup.ideation.models.ProblemStatement(/, **data)¶

Bases: pydantic.BaseModel

Defines a problem that the startup idea aims to solve.

This is the foundation of any good startup idea - a clear problem definition.

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.

Parameters:: data (Any)

model_config¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

property problem_score: float¶

Calculate a score for how good this problem is to solve.

Return type:: float

class prebuilt.startup.ideation.models.RiskAssessment(/, **data)¶

Bases: pydantic.BaseModel

Risk assessment for a startup idea.

Comprehensive risk analysis across multiple dimensions.

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.

Parameters:: data (Any)

calculate_overall_risk()¶: Calculate overall risk from individual components.

model_config¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class prebuilt.startup.ideation.models.RiskLevel¶

Bases: str, enum.Enum

Risk level assessment.

Initialize self. See help(type(self)) for accurate signature.

class prebuilt.startup.ideation.models.SolutionConcept(/, **data)¶

Bases: pydantic.BaseModel

Defines a solution concept for a problem.

This represents how the startup plans to solve the identified problem.

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.

Parameters:: data (Any)

classmethod validate_features(v)¶: Ensure we have at least 3 key features.

model_config¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class prebuilt.startup.ideation.models.StartupIdea(/, **data)¶

Bases: pydantic.BaseModel

Complete startup idea with all research and validation.

This is the main model that brings together all components of a startup idea.

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.

Parameters:: data (Any)

add_research(research_type, data)¶

Add research data to the idea.

Parameters:

research_type (str)
data (Any)

Return type:

None

add_validation(validation)¶

Add validation results.

Parameters:: validation (ValidationResult)
Return type:: None

calculate_readiness()¶

Calculate how ready this idea is for next steps.

Return type:: dict[str, Any]

get_research_gaps()¶

Identify what research is still needed.

Return type:: list[str]

to_pitch_deck_brief()¶

Convert idea to a brief for pitch deck generation.

This creates a structured brief that can be used by pitch deck agents.

Return type:: dict[str, Any]

update_timestamp()¶: Update timestamp on changes.

model_config¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class prebuilt.startup.ideation.models.ValidationMethod¶

Bases: str, enum.Enum

Methods for validating ideas.

Initialize self. See help(type(self)) for accurate signature.

class prebuilt.startup.ideation.models.ValidationResult(/, **data)¶

Bases: pydantic.BaseModel

Results from idea validation activities.

Tracks validation efforts and findings.

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.

Parameters:: data (Any)

model_config¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

prebuilt.startup.ideation.models.create_basic_idea(name, problem, solution, category)¶

Create a basic startup idea from minimal information.

Parameters:

name (str)
problem (str)
solution (str)
category (IdeaCategory)

Return type:

StartupIdea

prebuilt.startup.ideation.models.create_problem_from_description(description, severity='high')¶

Create a problem statement from a simple description.

Parameters:

description (str)
severity (str)

Return type:

ProblemStatement