
This is a configuration file for a Large Language Model (LLM) that appears to be used for generating content, specifically articles, based on provided queries and templates. The file contains several key components:
There are many exciting football matches today in Argentina where skill and tactics will be put to the test.
- Model and Temperature: The model used is LLMa-3.1-8b-instant, and the temperature is set to 0.7, which controls the level of creativity and randomness in the output.
- Columns to Add and Markdown Columns: The `columns_to_add` array specifies that two columns should be added to the output: “Outline” and “Text”. The `markdown_columns` array specifies that only the “Text” column should be formatted as Markdown.
- Queries: The `queries` object contains two keys: “Outline” and “Text”. The “Outline” query is used to generate a detailed SEO-optimized outline for an article, while the “Text” query is used to generate the final text of the article.
- Templates: The `templates` object contains several key-value pairs that define templates for the article. These templates include:
- `topic`: The topic of the article, which is “Topic: football matches today in Argentina”.
- `base_query`: The base query for the article, which is a long string containing a list of keywords related to football matches today in Argentina.
- `outline_info`: A template for generating an outline, which includes the title of the article and a link to the anchor.
- `intro`: A template for the introduction of the article, which instructs the LLM to act as a creative content strategist.
- `outln`: A template for generating the outline, which includes requirements for the outline, such as minimum sections, subpoints, and incorporation of keywords.
- `tekst`: A template for generating the final text of the article.
Based on this configuration file, the LLM will generate an article with a detailed SEO-optimized outline and a final text that meets the specified requirements.
