The problem
Headline generation must balance engaging language with enough source context to remain relevant and informative.
Approach
The Python application retrieves relevant examples from a headline dataset and adds them to the generation context. The language model then uses that retrieved material to produce a headline for the supplied content.
Focus
The project explored how retrieval-augmented generation can guide style while preserving a connection between the generated headline and its source material.
Outcome
Built a retrieval and generation workflow that supplies supporting examples and context before producing a headline.