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4923837165
* FIX: Llm selector / forced tools / search tool This fixes a few issues: 1. When search was not finding any semantic results we would break the tool 2. Gemin / Anthropic models did not implement forced tools previously despite it being an API option 3. Mechanics around displaying llm selector were not right. If you disabled LLM selector server side persona PM did not work correctly. 4. Disabling native tools for anthropic model moved out of a site setting. This deliberately does not migrate cause this feature is really rare to need now, people who had it set probably did not need it. 5. Updates anthropic model names to latest release * linting * fix a couple of tests I missed * clean up conditional
126 lines
3.6 KiB
Ruby
126 lines
3.6 KiB
Ruby
# frozen_string_literal: true
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module DiscourseAi
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module Completions
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module Endpoints
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class Anthropic < Base
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def self.can_contact?(model_provider)
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model_provider == "anthropic"
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end
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def normalize_model_params(model_params)
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# max_tokens, temperature, stop_sequences are already supported
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model_params
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end
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def default_options(dialect)
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mapped_model =
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case llm_model.name
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when "claude-2"
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"claude-2.1"
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when "claude-instant-1"
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"claude-instant-1.2"
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when "claude-3-haiku"
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"claude-3-haiku-20240307"
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when "claude-3-sonnet"
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"claude-3-sonnet-20240229"
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when "claude-3-opus"
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"claude-3-opus-20240229"
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when "claude-3-5-sonnet"
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"claude-3-5-sonnet-latest"
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else
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llm_model.name
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end
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options = { model: mapped_model, max_tokens: 3_000 }
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options[:stop_sequences] = ["</function_calls>"] if !dialect.native_tool_support? &&
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dialect.prompt.has_tools?
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options
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end
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def provider_id
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AiApiAuditLog::Provider::Anthropic
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end
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private
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def xml_tags_to_strip(dialect)
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if dialect.prompt.has_tools?
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%w[thinking search_quality_reflection search_quality_score]
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else
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[]
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end
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end
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# this is an approximation, we will update it later if request goes through
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def prompt_size(prompt)
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tokenizer.size(prompt.system_prompt.to_s + " " + prompt.messages.to_s)
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end
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def model_uri
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URI(llm_model.url)
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end
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def prepare_payload(prompt, model_params, dialect)
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@native_tool_support = dialect.native_tool_support?
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payload = default_options(dialect).merge(model_params).merge(messages: prompt.messages)
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payload[:system] = prompt.system_prompt if prompt.system_prompt.present?
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payload[:stream] = true if @streaming_mode
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if prompt.has_tools?
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payload[:tools] = prompt.tools
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if dialect.tool_choice.present?
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payload[:tool_choice] = { type: "tool", name: dialect.tool_choice }
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end
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end
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payload
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end
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def prepare_request(payload)
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headers = {
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"anthropic-version" => "2023-06-01",
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"x-api-key" => llm_model.api_key,
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"content-type" => "application/json",
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}
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Net::HTTP::Post.new(model_uri, headers).tap { |r| r.body = payload }
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end
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def processor
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@processor ||=
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DiscourseAi::Completions::AnthropicMessageProcessor.new(streaming_mode: @streaming_mode)
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end
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def add_to_function_buffer(function_buffer, partial: nil, payload: nil)
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processor.to_xml_tool_calls(function_buffer) if !partial
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end
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def extract_completion_from(response_raw)
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processor.process_message(response_raw)
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end
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def has_tool?(_response_data)
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processor.tool_calls.present?
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end
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def final_log_update(log)
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log.request_tokens = processor.input_tokens if processor.input_tokens
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log.response_tokens = processor.output_tokens if processor.output_tokens
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end
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def native_tool_support?
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@native_tool_support
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end
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def partials_from(decoded_chunk)
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decoded_chunk.split("\n").map { |line| line.split("data: ", 2)[1] }.compact
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end
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end
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end
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end
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end
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