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* UX: Validations to Llm-backed features (except AI Bot) This change is part of an ongoing effort to prevent enabling a broken feature due to lack of configuration. We also want to explicit which provider we are going to use. For example, Claude models are available through AWS Bedrock and Anthropic, but the configuration differs. Validations are: * You must choose a model before enabling the feature. * You must turn off the feature before setting the model to blank. * You must configure each model settings before being able to select it. * Add provider name to summarization options * vLLM can technically support same models as HF * Check we can talk to the selected model * Check for Bedrock instead of anthropic as a site could have both creds setup
193 lines
6.1 KiB
Ruby
193 lines
6.1 KiB
Ruby
# frozen_string_literal: true
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module DiscourseAi
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module AiBot
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class Bot
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BOT_NOT_FOUND = Class.new(StandardError)
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MAX_COMPLETIONS = 5
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def self.as(bot_user, persona: DiscourseAi::AiBot::Personas::General.new)
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new(bot_user, persona)
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end
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def initialize(bot_user, persona)
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@bot_user = bot_user
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@persona = persona
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end
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attr_reader :bot_user
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def get_updated_title(conversation_context, post_user)
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system_insts = <<~TEXT.strip
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You are titlebot. Given a topic, you will figure out a title.
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You will never respond with anything but 7 word topic title.
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TEXT
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title_prompt =
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DiscourseAi::Completions::Prompt.new(system_insts, messages: conversation_context)
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title_prompt.push(
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type: :user,
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content:
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"Based on our previous conversation, suggest a 7 word title without quoting any of it.",
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)
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DiscourseAi::Completions::Llm
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.proxy(model)
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.generate(title_prompt, user: post_user)
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.strip
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.split("\n")
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.last
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end
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def reply(context, &update_blk)
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prompt = persona.craft_prompt(context)
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total_completions = 0
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ongoing_chain = true
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low_cost = false
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raw_context = []
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while total_completions <= MAX_COMPLETIONS && ongoing_chain
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current_model = model(prefer_low_cost: low_cost)
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llm = DiscourseAi::Completions::Llm.proxy(current_model)
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tool_found = false
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result =
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llm.generate(prompt, user: context[:user]) do |partial, cancel|
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if (tool = persona.find_tool(partial))
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tool_found = true
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ongoing_chain = tool.chain_next_response?
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low_cost = tool.low_cost?
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tool_call_id = tool.tool_call_id
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invocation_result_json = invoke_tool(tool, llm, cancel, &update_blk).to_json
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tool_call_message = {
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type: :tool_call,
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id: tool_call_id,
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content: { name: tool.name, arguments: tool.parameters }.to_json,
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}
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tool_message = { type: :tool, id: tool_call_id, content: invocation_result_json }
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if tool.standalone?
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standalone_context =
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context.dup.merge(
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conversation_context: [
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context[:conversation_context].last,
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tool_call_message,
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tool_message,
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],
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)
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prompt = persona.craft_prompt(standalone_context)
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else
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prompt.push(**tool_call_message)
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prompt.push(**tool_message)
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end
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raw_context << [tool_call_message[:content], tool_call_id, "tool_call"]
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raw_context << [invocation_result_json, tool_call_id, "tool"]
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else
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update_blk.call(partial, cancel, nil)
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end
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end
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if !tool_found
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ongoing_chain = false
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raw_context << [result, bot_user.username]
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end
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total_completions += 1
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# do not allow tools when we are at the end of a chain (total_completions == MAX_COMPLETIONS)
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prompt.tools = [] if total_completions == MAX_COMPLETIONS
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end
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raw_context
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end
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attr_reader :persona
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private
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def invoke_tool(tool, llm, cancel, &update_blk)
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update_blk.call("", cancel, build_placeholder(tool.summary, ""))
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result =
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tool.invoke(bot_user, llm) do |progress|
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placeholder = build_placeholder(tool.summary, progress)
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update_blk.call("", cancel, placeholder)
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end
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tool_details = build_placeholder(tool.summary, tool.details, custom_raw: tool.custom_raw)
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update_blk.call(tool_details, cancel, nil)
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result
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end
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def model(prefer_low_cost: false)
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# HACK(roman): We'll do this until we define how we represent different providers in the bot settings
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default_model =
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case bot_user.id
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when DiscourseAi::AiBot::EntryPoint::CLAUDE_V2_ID
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if DiscourseAi::Completions::Endpoints::AwsBedrock.correctly_configured?("claude-2")
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"aws_bedrock:claude-2"
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else
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"anthropic:claude-2"
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end
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when DiscourseAi::AiBot::EntryPoint::GPT4_ID
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"open_ai:gpt-4"
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when DiscourseAi::AiBot::EntryPoint::GPT4_TURBO_ID
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"open_ai:gpt-4-turbo"
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when DiscourseAi::AiBot::EntryPoint::GPT3_5_TURBO_ID
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"open_ai:gpt-3.5-turbo-16k"
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when DiscourseAi::AiBot::EntryPoint::MIXTRAL_ID
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if DiscourseAi::Completions::Endpoints::Vllm.correctly_configured?(
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"mistralai/Mixtral-8x7B-Instruct-v0.1",
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)
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"vllm:mistralai/Mixtral-8x7B-Instruct-v0.1"
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else
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"hugging_face:mistralai/Mixtral-8x7B-Instruct-v0.1"
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end
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when DiscourseAi::AiBot::EntryPoint::GEMINI_ID
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"google:gemini-pro"
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when DiscourseAi::AiBot::EntryPoint::FAKE_ID
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"fake:fake"
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else
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nil
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end
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if %w[open_ai:gpt-4 open_ai:gpt-4-turbo].include?(default_model) && prefer_low_cost
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return "open_ai:gpt-3.5-turbo-16k"
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end
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default_model
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end
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def tool_invocation?(partial)
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Nokogiri::HTML5.fragment(partial).at("invoke").present?
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end
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def build_placeholder(summary, details, custom_raw: nil)
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placeholder = +(<<~HTML)
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<details>
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<summary>#{summary}</summary>
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<p>#{details}</p>
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</details>
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HTML
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if custom_raw
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placeholder << "\n"
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placeholder << custom_raw
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else
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# we need this for cursor placeholder to work
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# doing this in CSS is very hard
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# if changing test with a custom tool such as search
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placeholder << "<span></span>\n\n"
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end
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placeholder
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end
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end
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end
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end
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