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This makes it easier to cut and paste snippets it is producing Also fine tune the prompt in an attempt to hone gpt 3.5 which is very finicky
74 lines
2.2 KiB
Ruby
74 lines
2.2 KiB
Ruby
#frozen_string_literal: true
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module DiscourseAi
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module AiBot
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module Personas
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class SqlHelper < Persona
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def self.schema
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return @schema if defined?(@schema)
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tables = Hash.new
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priority_tables = %w[posts topics notifications users user_actions user_emails]
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DB.query(<<~SQL).each { |row| (tables[row.table_name] ||= []) << row.column_name }
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select table_name, column_name from information_schema.columns
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where table_schema = 'public'
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order by table_name
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SQL
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schema = +(priority_tables.map { |name| "#{name}(#{tables[name].join(",")})" }.join("\n"))
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schema << "\nOther tables (schema redacted, available on request): "
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tables.each do |table_name, _|
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next if priority_tables.include?(table_name)
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schema << "#{table_name} "
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end
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@schema = schema
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end
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def commands
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all_available_commands
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end
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def all_available_commands
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[DiscourseAi::AiBot::Commands::DbSchemaCommand]
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end
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def system_prompt
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<<~PROMPT
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You are a PostgreSQL expert.
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- You understand and generate Discourse Markdown but specialize in creating queries.
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- You live in a Discourse Forum Message.
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- The schema in your training set MAY be out of date.
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- When generating SQL NEVER end SQL samples with a semicolon (;).
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- When generating SQL always use ```sql markdown code blocks.
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- Always format SQL in a highly readable format.
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Eg:
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```sql
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select 1 from table
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```
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The user_actions tables stores likes (action_type 1).
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the topics table stores private/personal messages it uses archetype private_message for them.
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notification_level can be: {muted: 0, regular: 1, tracking: 2, watching: 3, watching_first_post: 4}.
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bookmarkable_type can be: Post,Topic,ChatMessage and more
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Current time is: {time}
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The current schema for the current DB is:
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{{
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#{self.class.schema}
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}}
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{commands}
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PROMPT
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end
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end
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end
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end
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end
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