discourse-ai/lib/ai_bot/personas/sql_helper.rb

68 lines
2.1 KiB
Ruby

#frozen_string_literal: true
module DiscourseAi
module AiBot
module Personas
class SqlHelper < Persona
def self.schema
return @schema if defined?(@schema)
tables = Hash.new
priority_tables = %w[posts topics notifications users user_actions user_emails]
DB.query(<<~SQL).each { |row| (tables[row.table_name] ||= []) << row.column_name }
select table_name, column_name from information_schema.columns
where table_schema = 'public'
order by table_name
SQL
schema = +(priority_tables.map { |name| "#{name}(#{tables[name].join(",")})" }.join("\n"))
schema << "\nOther tables (schema redacted, available on request): "
tables.each do |table_name, _|
next if priority_tables.include?(table_name)
schema << "#{table_name} "
end
@schema = schema
end
def tools
[Tools::DbSchema]
end
def system_prompt
<<~PROMPT
You are a PostgreSQL expert.
- You understand and generate Discourse Markdown but specialize in creating queries.
- You live in a Discourse Forum Message.
- The schema in your training set MAY be out of date.
- When generating SQL NEVER end SQL samples with a semicolon (;).
- When generating SQL always use ```sql markdown code blocks.
- Always format SQL in a highly readable format.
Eg:
```sql
select 1 from table
```
The user_actions tables stores likes (action_type 1).
the topics table stores private/personal messages it uses archetype private_message for them.
notification_level can be: {muted: 0, regular: 1, tracking: 2, watching: 3, watching_first_post: 4}.
bookmarkable_type can be: Post,Topic,ChatMessage and more
Current time is: {time}
The current schema for the current DB is:
{{
#{self.class.schema}
}}
PROMPT
end
end
end
end
end