Roman Rizzi 4f1a3effe0
REFACTOR: Migrate Vllm/TGI-served models to the OpenAI format. (#588)
Both endpoints provide OpenAI-compatible servers. The only difference is that Vllm doesn't support passing tools as a separate parameter. Even if the tool param is supported, it ultimately relies on the model's ability to handle native functions, which is not the case with the models we have today.

As a part of this change, we are dropping support for StableBeluga/Llama2 models. They don't have a chat_template, meaning the new API can translate them.

These changes let us remove some of our existing dialects and are a first step in our plan to support any LLM by defining them as data-driven concepts.

 I rewrote the "translate" method to use a template method and extracted the tool support strategies into its classes to simplify the code.

Finally, these changes bring support for Ollama when running in dev mode. It only works with Mistral for now, but it will change soon..
2024-05-07 10:02:16 -03:00

168 lines
4.5 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module Completions
module Dialects
class Dialect
class << self
def can_translate?(_model_name)
raise NotImplemented
end
def dialect_for(model_name)
dialects = [
DiscourseAi::Completions::Dialects::ChatGpt,
DiscourseAi::Completions::Dialects::Gemini,
DiscourseAi::Completions::Dialects::Mistral,
DiscourseAi::Completions::Dialects::Claude,
DiscourseAi::Completions::Dialects::Command,
]
if Rails.env.test? || Rails.env.development?
dialects << DiscourseAi::Completions::Dialects::Fake
end
dialect = dialects.find { |d| d.can_translate?(model_name) }
raise DiscourseAi::Completions::Llm::UNKNOWN_MODEL if !dialect
dialect
end
def tokenizer
raise NotImplemented
end
end
def initialize(generic_prompt, model_name, opts: {})
@prompt = generic_prompt
@model_name = model_name
@opts = opts
end
VALID_ID_REGEX = /\A[a-zA-Z0-9_]+\z/
def can_end_with_assistant_msg?
false
end
def native_tool_support?
false
end
def tools
@tools ||= tools_dialect.translated_tools
end
def translate
messages = prompt.messages
# Some models use an assistant msg to improve long-context responses.
if messages.last[:type] == :model && can_end_with_assistant_msg?
messages = messages.dup
messages.pop
end
trim_messages(messages).map { |msg| send("#{msg[:type]}_msg", msg) }.compact
end
def conversation_context
raise NotImplemented
end
def max_prompt_tokens
raise NotImplemented
end
attr_reader :prompt
private
attr_reader :model_name, :opts
def trim_messages(messages)
prompt_limit = max_prompt_tokens
current_token_count = 0
message_step_size = (max_prompt_tokens / 25).to_i * -1
trimmed_messages = []
range = (0..-1)
if messages.dig(0, :type) == :system
system_message = messages[0]
trimmed_messages << system_message
current_token_count += calculate_message_token(system_message)
range = (1..-1)
end
reversed_trimmed_msgs = []
messages[range].reverse.each do |msg|
break if current_token_count >= prompt_limit
message_tokens = calculate_message_token(msg)
dupped_msg = msg.dup
# Don't trim tool call metadata.
if msg[:type] == :tool_call
break if current_token_count + message_tokens + per_message_overhead > prompt_limit
current_token_count += message_tokens + per_message_overhead
reversed_trimmed_msgs << dupped_msg
next
end
# Trimming content to make sure we respect token limit.
while dupped_msg[:content].present? &&
message_tokens + current_token_count + per_message_overhead > prompt_limit
dupped_msg[:content] = dupped_msg[:content][0..message_step_size] || ""
message_tokens = calculate_message_token(dupped_msg)
end
next if dupped_msg[:content].blank?
current_token_count += message_tokens + per_message_overhead
reversed_trimmed_msgs << dupped_msg
end
reversed_trimmed_msgs.pop if reversed_trimmed_msgs.last&.dig(:type) == :tool
trimmed_messages.concat(reversed_trimmed_msgs.reverse)
end
def per_message_overhead
0
end
def calculate_message_token(msg)
self.class.tokenizer.size(msg[:content].to_s)
end
def tools_dialect
@tools_dialect ||= DiscourseAi::Completions::Dialects::XmlTools.new(prompt.tools)
end
def system_msg(msg)
raise NotImplemented
end
def assistant_msg(msg)
raise NotImplemented
end
def user_msg(msg)
raise NotImplemented
end
def tool_call_msg(msg)
{ role: "assistant", content: tools_dialect.from_raw_tool_call(msg) }
end
def tool_msg(msg)
{ role: "user", content: tools_dialect.from_raw_tool(msg) }
end
end
end
end
end