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# frozen_string_literal: true
module DiscourseAi
module Admin
class AiLlmsController < ::Admin::AdminController
requires_plugin ::DiscourseAi::PLUGIN_NAME
def index
llms = LlmModel.all.includes(:llm_quotas).order(:display_name)
render json: {
ai_llms:
ActiveModel::ArraySerializer.new(
llms,
each_serializer: LlmModelSerializer,
root: false,
scope: {
llm_usage: DiscourseAi::Configuration::LlmEnumerator.global_usage,
},
).as_json,
meta: {
provider_params: LlmModel.provider_params,
presets: DiscourseAi::Completions::Llm.presets,
providers: DiscourseAi::Completions::Llm.provider_names,
tokenizers:
DiscourseAi::Completions::Llm.tokenizer_names.map { |tn|
{ id: tn, name: tn.split("::").last }
},
},
}
end
def new
end
def edit
llm_model = LlmModel.find(params[:id])
render json: LlmModelSerializer.new(llm_model)
end
def create
llm_model = LlmModel.new(ai_llm_params)
# we could do nested attributes but the mechanics are not ideal leading
# to lots of complex debugging, this is simpler
quota_params.each { |quota| llm_model.llm_quotas.build(quota) } if quota_params
if llm_model.save
llm_model.toggle_companion_user
log_llm_model_creation(llm_model)
render json: LlmModelSerializer.new(llm_model), status: :created
else
render_json_error llm_model
end
end
def update
llm_model = LlmModel.find(params[:id])
# Capture initial state for logging
initial_attributes = llm_model.attributes.dup
initial_quotas = llm_model.llm_quotas.map(&:attributes)
if params[:ai_llm].key?(:llm_quotas)
if quota_params
existing_quota_group_ids = llm_model.llm_quotas.pluck(:group_id)
new_quota_group_ids = quota_params.map { |q| q[:group_id] }
llm_model
.llm_quotas
.where(group_id: existing_quota_group_ids - new_quota_group_ids)
.destroy_all
quota_params.each do |quota_param|
quota = llm_model.llm_quotas.find_or_initialize_by(group_id: quota_param[:group_id])
quota.update!(quota_param)
end
else
llm_model.llm_quotas.destroy_all
end
end
if llm_model.seeded?
return render_json_error(I18n.t("discourse_ai.llm.cannot_edit_builtin"), status: 403)
end
if llm_model.update(ai_llm_params(updating: llm_model))
llm_model.toggle_companion_user
log_llm_model_update(llm_model, initial_attributes, initial_quotas)
render json: LlmModelSerializer.new(llm_model)
else
render_json_error llm_model
end
end
def destroy
llm_model = LlmModel.find(params[:id])
if llm_model.seeded?
return render_json_error(I18n.t("discourse_ai.llm.cannot_delete_builtin"), status: 403)
end
in_use_by = DiscourseAi::Configuration::LlmValidator.new.modules_using(llm_model)
if !in_use_by.empty?
return(
render_json_error(
I18n.t(
"discourse_ai.llm.delete_failed",
settings: in_use_by.join(", "),
count: in_use_by.length,
),
status: 409,
)
)
end
# Capture model details for logging before destruction
model_details = {
model_id: llm_model.id,
display_name: llm_model.display_name,
name: llm_model.name,
provider: llm_model.provider,
}
# Clean up companion users
llm_model.enabled_chat_bot = false
llm_model.toggle_companion_user
if llm_model.destroy
log_llm_model_deletion(model_details)
head :no_content
else
render_json_error llm_model
end
end
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def test
RateLimiter.new(current_user, "llm_test_#{current_user.id}", 3, 1.minute).performed!
llm_model = LlmModel.new(ai_llm_params)
DiscourseAi::Configuration::LlmValidator.new.run_test(llm_model)
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render json: { success: true }
rescue DiscourseAi::Completions::Endpoints::Base::CompletionFailed => e
render json: { success: false, error: e.message }
end
private
def quota_params
if params[:ai_llm][:llm_quotas].present?
params[:ai_llm][:llm_quotas].map do |quota|
mapped = {}
mapped[:group_id] = quota[:group_id].to_i
mapped[:max_tokens] = quota[:max_tokens].to_i if quota[:max_tokens].present?
mapped[:max_usages] = quota[:max_usages].to_i if quota[:max_usages].present?
mapped[:duration_seconds] = quota[:duration_seconds].to_i
mapped
end
end
end
def ai_llm_params(updating: nil)
return {} if params[:ai_llm].blank?
permitted =
params.require(:ai_llm).permit(
:display_name,
:name,
:provider,
:tokenizer,
:max_prompt_tokens,
:max_output_tokens,
:api_key,
:enabled_chat_bot,
:vision_enabled,
:input_cost,
:cached_input_cost,
:output_cost,
)
provider = updating ? updating.provider : permitted[:provider]
permit_url = provider != LlmModel::BEDROCK_PROVIDER_NAME
new_url = params.dig(:ai_llm, :url)
permitted[:url] = new_url if permit_url && new_url
extra_field_names = LlmModel.provider_params.dig(provider&.to_sym)
if extra_field_names.present?
received_prov_params =
params.dig(:ai_llm, :provider_params)&.slice(*extra_field_names.keys)
if received_prov_params.present?
received_prov_params.each do |pname, value|
if extra_field_names[pname.to_sym] == :checkbox
received_prov_params[pname] = ActiveModel::Type::Boolean.new.cast(value)
end
end
permitted[:provider_params] = received_prov_params.permit!
end
end
permitted
end
def ai_llm_logger_fields
{
display_name: {
},
name: {
},
provider: {
},
tokenizer: {
},
url: {
},
max_prompt_tokens: {
},
max_output_tokens: {
},
enabled_chat_bot: {
},
vision_enabled: {
},
api_key: {
type: :sensitive,
},
input_cost: {
},
output_cost: {
},
# JSON fields should be tracked as simple changes
json_fields: [:provider_params],
}
end
def log_llm_model_creation(llm_model)
logger = DiscourseAi::Utils::AiStaffActionLogger.new(current_user)
entity_details = { model_id: llm_model.id, subject: llm_model.display_name }
# Add quota information as a special case
if llm_model.llm_quotas.any?
entity_details[:quotas] = llm_model
.llm_quotas
.map do |quota|
"Group #{quota.group_id}: #{quota.max_tokens} tokens, #{quota.max_usages} usages, #{quota.duration_seconds}s"
end
.join("; ")
end
logger.log_creation("llm_model", llm_model, ai_llm_logger_fields, entity_details)
end
def log_llm_model_update(llm_model, initial_attributes, initial_quotas)
logger = DiscourseAi::Utils::AiStaffActionLogger.new(current_user)
entity_details = { model_id: llm_model.id, subject: llm_model.display_name }
# Track quota changes separately as they're a special case
current_quotas = llm_model.llm_quotas.reload.map(&:attributes)
if initial_quotas != current_quotas
initial_quota_summary =
initial_quotas
.map { |q| "Group #{q["group_id"]}: #{q["max_tokens"]} tokens" }
.join("; ")
current_quota_summary =
current_quotas
.map { |q| "Group #{q["group_id"]}: #{q["max_tokens"]} tokens" }
.join("; ")
entity_details[:quotas_changed] = true
entity_details[:quotas] = "#{initial_quota_summary}#{current_quota_summary}"
end
logger.log_update(
"llm_model",
llm_model,
initial_attributes,
ai_llm_logger_fields,
entity_details,
)
end
def log_llm_model_deletion(model_details)
logger = DiscourseAi::Utils::AiStaffActionLogger.new(current_user)
model_details[:subject] = model_details[:display_name]
logger.log_deletion("llm_model", model_details)
end
end
end
end