prebuilt.journalism_.engines¶

Engine configurations for the Journalism AI Assistant.

This module defines all AugLLMConfig engines used by the journalism assistant for various analysis tasks including summarization, fact-checking, tone analysis, quote extraction, and grammar/bias review.

Each engine is configured with specific prompts, tools, and output models to handle different aspects of journalism analysis.

Example

>>> from journalism_assistant.engines import create_summarization_engine
>>> summary_engine = create_summarization_engine()
>>> result = summary_engine.invoke(state)

Note

All engines use structured_output_version=’v2’ for Pydantic v2 compatibility.

Functions¶

`create_action_identification_engine`()	Create engine for identifying user-requested actions.
`create_summarization_engine`()	Create engine for article summarization.

Module Contents¶

prebuilt.journalism_.engines.create_action_identification_engine()¶

Create engine for identifying user-requested actions.

This engine analyzes user input to determine which journalism analysis actions should be performed.

Returns:: Configured action identification engine
Return type:: AugLLMConfig

prebuilt.journalism_.engines.create_summarization_engine()¶

Create engine for article summarization.

This engine generates concise summaries focusing on main events, key people, and important statistics.

Returns:: Configured summarization engine
Return type:: AugLLMConfig