discourse-ai/lib/completions/endpoints/gemini.rb

185 lines
4.9 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module Completions
module Endpoints
class Gemini < Base
def self.can_contact?(model_provider)
model_provider == "google"
end
def default_options
# the default setting is a problem, it blocks too much
categories = %w[HARASSMENT SEXUALLY_EXPLICIT HATE_SPEECH DANGEROUS_CONTENT]
safety_settings =
categories.map do |category|
{ category: "HARM_CATEGORY_#{category}", threshold: "BLOCK_NONE" }
end
{ generationConfig: {}, safetySettings: safety_settings }
end
def normalize_model_params(model_params)
model_params = model_params.dup
if model_params[:stop_sequences]
model_params[:stopSequences] = model_params.delete(:stop_sequences)
end
if model_params[:max_tokens]
model_params[:maxOutputTokens] = model_params.delete(:max_tokens)
end
model_params[:topP] = model_params.delete(:top_p) if model_params[:top_p]
# temperature already supported
model_params
end
def provider_id
AiApiAuditLog::Provider::Gemini
end
private
def model_uri
url = llm_model.url
key = llm_model.api_key
if @streaming_mode
url = "#{url}:streamGenerateContent?key=#{key}&alt=sse"
else
url = "#{url}:generateContent?key=#{key}"
end
URI(url)
end
def prepare_payload(prompt, model_params, dialect)
tools = dialect.tools
payload = default_options.merge(contents: prompt[:messages])
payload[:systemInstruction] = {
role: "system",
parts: [{ text: prompt[:system_instruction].to_s }],
} if prompt[:system_instruction].present?
if tools.present?
payload[:tools] = tools
payload[:tool_config] = { function_calling_config: { mode: "AUTO" } }
end
payload[:generationConfig].merge!(model_params) if model_params.present?
payload
end
def prepare_request(payload)
headers = { "Content-Type" => "application/json" }
Net::HTTP::Post.new(model_uri, headers).tap { |r| r.body = payload }
end
def extract_completion_from(response_raw)
parsed =
if @streaming_mode
response_raw
else
JSON.parse(response_raw, symbolize_names: true)
end
response_h = parsed.dig(:candidates, 0, :content, :parts, 0)
@has_function_call ||= response_h.dig(:functionCall).present?
@has_function_call ? response_h[:functionCall] : response_h.dig(:text)
end
def partials_from(decoded_chunk)
decoded_chunk
end
def chunk_to_string(chunk)
chunk.to_s
end
class Decoder
def initialize
@buffer = +""
end
def decode(str)
@buffer << str
lines = @buffer.split(/\r?\n\r?\n/)
keep_last = false
decoded =
lines
.map do |line|
if line.start_with?("data: {")
begin
JSON.parse(line[6..-1], symbolize_names: true)
rescue JSON::ParserError
keep_last = line
nil
end
else
keep_last = line
nil
end
end
.compact
if keep_last
@buffer = +(keep_last)
else
@buffer = +""
end
decoded
end
end
def decode(chunk)
@decoder ||= Decoder.new
@decoder.decode(chunk)
end
def extract_prompt_for_tokenizer(prompt)
prompt.to_s
end
def has_tool?(_response_data)
@has_function_call
end
def native_tool_support?
true
end
def add_to_function_buffer(function_buffer, payload: nil, partial: nil)
if @streaming_mode
return function_buffer if !partial
else
partial = payload
end
function_buffer.at("tool_name").content = partial[:name] if partial[:name].present?
if partial[:args]
argument_fragments =
partial[:args].reduce(+"") do |memo, (arg_name, value)|
memo << "\n<#{arg_name}>#{value}</#{arg_name}>"
end
argument_fragments << "\n"
function_buffer.at("parameters").children =
Nokogiri::HTML5::DocumentFragment.parse(argument_fragments)
end
function_buffer
end
end
end
end
end