discourse-ai/lib/completions/dialects/orca_style.rb

74 lines
1.9 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module Completions
module Dialects
class OrcaStyle < Dialect
class << self
def can_translate?(model_name)
%w[StableBeluga2 Upstage-Llama-2-*-instruct-v2].include?(model_name)
end
def tokenizer
DiscourseAi::Tokenizer::Llama2Tokenizer
end
end
def translate
orca_style_prompt = +<<~TEXT
### System:
#{prompt[:insts]}
#{build_tools_prompt}#{prompt[:post_insts]}
TEXT
if prompt[:examples]
prompt[:examples].each do |example_pair|
orca_style_prompt << "### User:\n#{example_pair.first}\n"
orca_style_prompt << "### Assistant:\n#{example_pair.second}\n"
end
end
orca_style_prompt << "### User:\n#{prompt[:input]}\n"
orca_style_prompt << "### Assistant:\n"
end
def conversation_context
return "" if prompt[:conversation_context].blank?
trimmed_context = trim_context(prompt[:conversation_context])
trimmed_context
.reverse
.reduce(+"") do |memo, context|
next(memo) if context[:type] == "tool_call"
memo << (context[:type] == "user" ? "### User:" : "### Assistant:")
if context[:type] == "tool"
memo << <<~TEXT
<function_results>
<result>
<tool_name>#{context[:name]}</tool_name>
<json>
#{context[:content]}
</json>
</result>
</function_results>
TEXT
else
memo << " " << context[:content] << "\n"
end
memo
end
end
def max_prompt_tokens
SiteSetting.ai_hugging_face_token_limit
end
end
end
end
end