prebuilt.journalism_.models¶

Models for the Journalism AI Assistant.

This module defines all Pydantic models used by the journalism assistant for structured outputs, validation, and data handling throughout the fact-checking, analysis, and review workflows.

Examples

>>> from journalism_assistant.models import FactCheckStatement, ArticleSummary
>>> fact_check = FactCheckStatement(
...     statement="The economy grew by 3%",
...     status="confirmed",
...     explanation="Verified by official statistics"
... )

Note

All models use Pydantic v2 with comprehensive field descriptions for documentation and validation.

Classes¶

`ArticleChunk`	Chunk of article text for processing.
`ArticleSummary`	Structured summary of an article.
`BiasIndicator`	Potential bias indicator in the text.
`ComprehensiveReport`	Complete journalism analysis report.
`ExtractedQuote`	Individual quote extracted from an article.
`FactCheckResult`	Complete fact-checking results for an article.
`FactCheckStatement`	Individual fact-check result for a single statement.
`GrammarBiasReview`	Complete grammar and bias review results.
`GrammarIssue`	Individual grammar or style issue.
`JournalismAction`	User action request for journalism tasks.
`QuoteExtractionResult`	Complete quote extraction results.
`SearchResult`	Web search result for fact-checking.
`ToneAnalysis`	Analysis of article tone and sentiment.

Module Contents¶

class prebuilt.journalism_.models.ArticleChunk(/, **data)¶

Bases: pydantic.BaseModel

Chunk of article text for processing.

Represents a portion of the article for processing within token limits.

Parameters:: data (Any)

chunk_id¶: Unique identifier for the chunk

text¶: The actual text content

start_position¶: Starting character position

end_position¶: Ending character position

word_count¶: Number of words in chunk

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.

validate_positions()¶

Ensure end position is after start position.

Return type:: ArticleChunk

class prebuilt.journalism_.models.ArticleSummary(/, **data)¶

Bases: pydantic.BaseModel

Structured summary of an article.

Provides a comprehensive summary focusing on key events, people, and statistics.

Parameters:: data (Any)

main_points¶: List of main points from the article

key_people¶: Important people mentioned

key_statistics¶: Important numbers and data

word_count¶: Original article word count

summary_text¶: Complete summary in paragraph form

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 prebuilt.journalism_.models.BiasIndicator(/, **data)¶

Bases: pydantic.BaseModel

Potential bias indicator in the text.

Represents language or framing that may indicate bias.

Parameters:: data (Any)

bias_type¶: Type of bias detected

example_text¶: Text showing the bias

explanation¶: Why this indicates bias

severity¶: How severe the bias is

suggestion¶: How to make it more neutral

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 prebuilt.journalism_.models.ComprehensiveReport(/, **data)¶

Bases: pydantic.BaseModel

Complete journalism analysis report.

Combines all analysis results into a comprehensive report.

Parameters:: data (Any)

article_title¶: Title of the analyzed article

analysis_timestamp¶: When the analysis was performed

summary¶: Article summary

fact_check_results¶: Fact-checking results

tone_analysis¶: Tone and sentiment analysis

quotes¶: Extracted quotes

grammar_bias_review¶: Grammar and bias review

overall_assessment¶: Overall article assessment

recommendations¶: Recommendations for the article

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.

to_markdown()¶

Convert report to markdown format.

Returns:: Formatted markdown report
Return type:: str

class prebuilt.journalism_.models.ExtractedQuote(/, **data)¶

Bases: pydantic.BaseModel

Individual quote extracted from an article.

Represents a direct quote with attribution and context.

Parameters:: data (Any)

quote_text¶: The exact quoted text

speaker¶: Person who said the quote

context¶: Context or situation of the quote

position¶: Position/title of the speaker if mentioned

significance¶: Why this quote is important

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 prebuilt.journalism_.models.FactCheckResult(/, **data)¶

Bases: pydantic.BaseModel

Complete fact-checking results for an article.

Contains all fact-check statements and overall statistics about the verification process.

Parameters:: data (Any)

statements¶: List of individual fact-check results

total_claims¶: Total number of claims analyzed

confirmed_count¶: Number of confirmed claims

refuted_count¶: Number of refuted claims

unverifiable_count¶: Number of unverifiable claims

vague_count¶: Number of vague claims

overall_credibility¶: Overall credibility score

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.

calculate_statistics()¶

Calculate statistics from statements.

Return type:: FactCheckResult

class prebuilt.journalism_.models.FactCheckStatement(/, **data)¶

Bases: pydantic.BaseModel

Individual fact-check result for a single statement.

Represents the verification status of a claim or statement extracted from an article.

Parameters:: data (Any)

statement¶: The original claim being fact-checked

status¶: Verification status (confirmed/refuted/unverifiable/vague)

explanation¶: Detailed explanation of the verification result

suggested_keywords¶: Keywords for further research if needed

confidence¶: Confidence score in the fact-check result

sources¶: Supporting sources used for verification

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.

classmethod validate_keywords(v)¶

Ensure keywords are unique and non-empty.

Parameters:: v (List[str])
Return type:: List[str]

class prebuilt.journalism_.models.GrammarBiasReview(/, **data)¶

Bases: pydantic.BaseModel

Complete grammar and bias review results.

Comprehensive review covering grammar issues and potential biases.

Parameters:: data (Any)

grammar_issues¶: List of grammar/style issues found

bias_indicators¶: List of potential biases detected

overall_quality_score¶: Overall writing quality score

readability_score¶: Readability score

bias_score¶: Overall bias score

recommendations¶: General recommendations for improvement

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 prebuilt.journalism_.models.GrammarIssue(/, **data)¶

Bases: pydantic.BaseModel

Individual grammar or style issue.

Represents a specific grammar, spelling, or style problem found in the text.

Parameters:: data (Any)

issue_type¶: Type of issue found

text¶: The problematic text

suggestion¶: Suggested correction

severity¶: Severity level of the issue

location¶: Approximate location in the text

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 prebuilt.journalism_.models.JournalismAction(/, **data)¶

Bases: pydantic.BaseModel

User action request for journalism tasks.

Represents what actions the user wants to perform on the article.

Parameters:: data (Any)

actions¶: List of requested actions

priority¶: Priority level for the request

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 prebuilt.journalism_.models.QuoteExtractionResult(/, **data)¶

Bases: pydantic.BaseModel

Complete quote extraction results.

Contains all extracted quotes with metadata about the extraction process.

Parameters:: data (Any)

quotes¶: List of extracted quotes

total_quotes¶: Total number of quotes found

unique_speakers¶: Number of unique speakers

has_attribution¶: Whether all quotes have proper attribution

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.

calculate_quote_stats()¶

Calculate statistics from quotes.

Return type:: QuoteExtractionResult

class prebuilt.journalism_.models.SearchResult(/, **data)¶

Bases: pydantic.BaseModel

Web search result for fact-checking.

Represents a single search result used for verification.

Parameters:: data (Any)

title¶: Title of the search result

url¶: URL of the source

snippet¶: Brief excerpt from the page

relevance_score¶: How relevant this result is

credibility_score¶: Source credibility score

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 prebuilt.journalism_.models.ToneAnalysis(/, **data)¶

Bases: pydantic.BaseModel

Analysis of article tone and sentiment.

Evaluates the overall tone, sentiment, and potential biases present in the article.

Parameters:: data (Any)

overall_tone¶: Primary tone of the article

sentiment_score¶: Sentiment score (-1 to 1)

tone_examples¶: Specific examples supporting the analysis

detected_biases¶: List of potential biases found

objectivity_score¶: Score for journalistic objectivity

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.