Text summarization with LLMs and spacy-llm
Each spacy-llm component has a task definition. spaCy has some pre-defined tasks, and we can also create own tasks. In this section, we’re going to use the spacy.Summarization.v1 task. Each task is defined using a prompt. Here is the prompt for this task, available at https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/summarization.v1.jinja:
You are an expert summarization system. Your task is to accept Text as input and summarize the Text in a concise way.
{%- if max_n_words -%}
{# whitespace #}
The summary must not, under any circumstances, contain more than {{ max_n_words }} words.
{%- endif -%}
{# whitespace #}
{%- if prompt_examples -%}
{# whitespace #}
Below are some examples (only use these as a guide):
{# whitespace #}
{%- for example in prompt_examples -%}
{# whitespace #}
Text:
'''
{{ example.text }}
'''
Summary:
'''
{{ example.summary }}
''...
