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https://github.com/discourse/discourse-ai.git
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e0bf6adb5b
This PR adds tool support to available LLMs. We'll buffer tool invocations and return them instead of making users of this service parse the response. It also adds support for conversation context in the generic prompt. It includes bot messages, user messages, and tool invocations, which we'll trim to make sure it doesn't exceed the prompt limit, then translate them to the correct dialect. Finally, It adds some buffering when reading chunks to handle cases when streaming is extremely slow.:M
107 lines
2.9 KiB
Ruby
107 lines
2.9 KiB
Ruby
# frozen_string_literal: true
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require_relative "endpoint_examples"
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RSpec.describe DiscourseAi::Completions::Endpoints::HuggingFace do
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subject(:model) { described_class.new(model_name, DiscourseAi::Tokenizer::Llama2Tokenizer) }
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let(:model_name) { "Llama2-*-chat-hf" }
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let(:generic_prompt) { { insts: "You are a helpful bot.", input: "write 3 words" } }
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let(:dialect) do
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DiscourseAi::Completions::Dialects::Llama2Classic.new(generic_prompt, model_name)
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end
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let(:prompt) { dialect.translate }
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let(:request_body) do
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model
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.default_options
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.merge(inputs: prompt)
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.tap do |payload|
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payload[:parameters][:max_new_tokens] = (SiteSetting.ai_hugging_face_token_limit || 4_000) -
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model.prompt_size(prompt)
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end
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.to_json
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end
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let(:stream_request_body) do
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model
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.default_options
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.merge(inputs: prompt)
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.tap do |payload|
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payload[:parameters][:max_new_tokens] = (SiteSetting.ai_hugging_face_token_limit || 4_000) -
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model.prompt_size(prompt)
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payload[:stream] = true
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end
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.to_json
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end
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before { SiteSetting.ai_hugging_face_api_url = "https://test.dev" }
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def response(content)
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[{ generated_text: content }]
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end
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def stub_response(prompt, response_text, tool_call: false)
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WebMock
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.stub_request(:post, "#{SiteSetting.ai_hugging_face_api_url}")
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.with(body: request_body)
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.to_return(status: 200, body: JSON.dump(response(response_text)))
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end
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def stream_line(delta, deltas, finish_reason: nil)
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+"data: " << {
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token: {
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id: 29_889,
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text: delta,
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logprob: -0.08319092,
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special: !!finish_reason,
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},
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generated_text: finish_reason ? deltas.join : nil,
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details: nil,
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}.to_json
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end
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def stub_streamed_response(prompt, deltas, tool_call: false)
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chunks =
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deltas.each_with_index.map do |_, index|
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if index == (deltas.length - 1)
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stream_line(deltas[index], deltas, finish_reason: true)
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else
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stream_line(deltas[index], deltas)
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end
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end
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chunks = (chunks.join("\n\n") << "data: [DONE]").split("")
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WebMock
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.stub_request(:post, "#{SiteSetting.ai_hugging_face_api_url}")
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.with(body: stream_request_body)
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.to_return(status: 200, body: chunks)
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end
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let(:tool_deltas) { ["<function", <<~REPLY, <<~REPLY] }
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_calls>
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<invoke>
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<tool_name>get_weather</tool_name>
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<parameters>
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<location>Sydney</location>
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<unit>c</unit>
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</parameters>
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</invoke>
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</function_calls>
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REPLY
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<function_calls>
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<invoke>
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<tool_name>get_weather</tool_name>
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<parameters>
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<location>Sydney</location>
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<unit>c</unit>
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</parameters>
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</invoke>
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</function_calls>
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REPLY
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let(:tool_call) { invocation }
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it_behaves_like "an endpoint that can communicate with a completion service"
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end
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