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d26c7ac48d
This update adds metrics for estimated spending in AI usage. To make use of it, admins must add cost details to the LLM config page (input, output, and cached input costs per 1M tokens). After doing so, the metrics will appear in the AI usage dashboard as the AI plugin is used.
54 lines
1.3 KiB
Ruby
54 lines
1.3 KiB
Ruby
# frozen_string_literal: true
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class LlmModelSerializer < ApplicationSerializer
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# TODO: we probably should rename the table LlmModel to AiLlm
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# it is consistent with AiPersona and AiTool
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# LLM model is a bit confusing given that large langauge model model is a confusing
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# name
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root "ai_llm"
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attributes :id,
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:display_name,
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:name,
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:provider,
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:max_prompt_tokens,
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:max_output_tokens,
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:tokenizer,
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:api_key,
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:url,
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:enabled_chat_bot,
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:provider_params,
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:vision_enabled,
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:input_cost,
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:output_cost,
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:cached_input_cost,
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:used_by
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has_one :user, serializer: BasicUserSerializer, embed: :object
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has_many :llm_quotas, serializer: LlmQuotaSerializer, embed: :objects
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def used_by
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llm_usage =
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(
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if (scope && scope[:llm_usage])
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scope[:llm_usage]
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else
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DiscourseAi::Configuration::LlmEnumerator.global_usage
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end
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)
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llm_usage[object.id]
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end
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def api_key
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object.seeded? ? "********" : object.api_key
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end
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def url
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object.seeded? ? "********" : object.url
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end
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def provider
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object.seeded? ? "CDCK" : object.provider
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end
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end
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