prebuilt.ai_insight.models

Models for General News Reporter System.

Classes

Article

Represents a news article.

ArticleSummary

Summary of an article.

NewsCategory

Category for organizing news.

NewsReport

Complete news report.

NewsSearchConfig

Configuration for news search.

ReportConfig

Configuration for report generation.

ReportMetadata

Metadata for the news report.

SummaryStyle

Configuration for summary generation.

Module Contents

class prebuilt.ai_insight.models.Article(/, **data: Any)

Bases: pydantic.BaseModel

Represents a news article.

author: str | None = None
content: str = None
property days_old: int | None

Days since publication.

published_date: datetime.datetime | None = None
relevance_score: float = None
source: str = None
title: str = None
url: pydantic.HttpUrl = None
class prebuilt.ai_insight.models.ArticleSummary(/, **data: Any)

Bases: pydantic.BaseModel

Summary of an article.

category: str | None = None
implications: str | None = None
key_points: List[str] = None
source: str = None
summary: str = None
title: str = None
url: pydantic.HttpUrl = None
class prebuilt.ai_insight.models.NewsCategory(/, **data: Any)

Bases: pydantic.BaseModel

Category for organizing news.

property article_count: int

Number of articles in category.

articles: List[ArticleSummary] = None
description: str = None
name: str = None
class prebuilt.ai_insight.models.NewsReport(/, **data: Any)

Bases: pydantic.BaseModel

Complete news report.

categories: List[NewsCategory] = None
conclusion: str | None = None
executive_summary: str = None
introduction: str = None
metadata: ReportMetadata = None
property report_date: str

Formatted report date.

spotlight_article: ArticleSummary | None = None
subtitle: str | None = None
title: str = None
property total_articles: int

Total number of articles in report.

class prebuilt.ai_insight.models.NewsSearchConfig(/, **data: Any)

Bases: pydantic.BaseModel

Configuration for news search.

language: str = None
max_results: int = None
search_depth: Literal['basic', 'advanced'] = None
search_type: Literal['news', 'general', 'academic', 'business'] = None
time_period: Literal['1d', '3d', '1w', '1m', '3m'] = None
topic: str = None
class prebuilt.ai_insight.models.ReportConfig(/, **data: Any)

Bases: pydantic.BaseModel

Configuration for report generation.

articles_per_category: int = None
filename_pattern: str = None
include_spotlight: bool = None
max_categories: int = None
output_format: Literal['markdown', 'html', 'json'] = None
report_style: Literal['newsletter', 'brief', 'comprehensive', 'executive'] = None
save_to_file: bool = None
class prebuilt.ai_insight.models.ReportMetadata(/, **data: Any)

Bases: pydantic.BaseModel

Metadata for the news report.

generation_time: datetime.datetime = None
search_config: NewsSearchConfig = None
time_period: str = None
topic: str = None
total_sources: int = None
class prebuilt.ai_insight.models.SummaryStyle(/, **data: Any)

Bases: pydantic.BaseModel

Configuration for summary generation.

focus_areas: List[str] | None = None
include_implications: bool = None
length: Literal['brief', 'standard', 'detailed'] = None
simplify_technical: bool = None
target_audience: Literal['general', 'technical', 'executive', 'academic', 'youth'] = None