discourse-ai/lib/ai_bot/bot.rb

233 lines
7.1 KiB
Ruby

# frozen_string_literal: true
module DiscourseAi
module AiBot
class Bot
attr_reader :model
BOT_NOT_FOUND = Class.new(StandardError)
MAX_COMPLETIONS = 5
MAX_TOOLS = 5
def self.as(bot_user, persona: DiscourseAi::AiBot::Personas::General.new, model: nil)
new(bot_user, persona, model)
end
def initialize(bot_user, persona, model = nil)
@bot_user = bot_user
@persona = persona
@model = model || self.class.guess_model(bot_user) || @persona.class.default_llm
end
attr_reader :bot_user
attr_accessor :persona
def get_updated_title(conversation_context, post)
system_insts = <<~TEXT.strip
You are titlebot. Given a conversation, you will suggest a title.
- You will never respond with anything but the suggested title.
- You will always match the conversation language in your title suggestion.
- Title will capture the essence of the conversation.
TEXT
# conversation context may contain tool calls, and confusing user names
# clean it up
conversation = +""
conversation_context.each do |context|
if context[:type] == :user
conversation << "User said:\n#{context[:content]}\n\n"
elsif context[:type] == :model
conversation << "Model said:\n#{context[:content]}\n\n"
end
end
instruction = <<~TEXT.strip
Given the following conversation:
{{{
#{conversation}
}}}
Reply only with a title that is 7 words or less.
TEXT
title_prompt =
DiscourseAi::Completions::Prompt.new(
system_insts,
messages: [type: :user, content: instruction],
topic_id: post.topic_id,
)
DiscourseAi::Completions::Llm
.proxy(model)
.generate(title_prompt, user: post.user, feature_name: "bot_title")
.strip
.split("\n")
.last
end
def force_tool_if_needed(prompt, context)
context[:chosen_tools] ||= []
forced_tools = persona.force_tool_use.map { |tool| tool.name }
force_tool = forced_tools.find { |name| !context[:chosen_tools].include?(name) }
if force_tool && persona.forced_tool_count > 0
user_turns = prompt.messages.select { |m| m[:type] == :user }.length
force_tool = false if user_turns > persona.forced_tool_count
end
if force_tool
context[:chosen_tools] << force_tool
prompt.tool_choice = force_tool
else
prompt.tool_choice = nil
end
end
def reply(context, &update_blk)
llm = DiscourseAi::Completions::Llm.proxy(model)
prompt = persona.craft_prompt(context, llm: llm)
total_completions = 0
ongoing_chain = true
raw_context = []
user = context[:user]
llm_kwargs = { user: user }
llm_kwargs[:temperature] = persona.temperature if persona.temperature
llm_kwargs[:top_p] = persona.top_p if persona.top_p
needs_newlines = false
while total_completions <= MAX_COMPLETIONS && ongoing_chain
tool_found = false
force_tool_if_needed(prompt, context)
result =
llm.generate(prompt, feature_name: "bot", **llm_kwargs) do |partial, cancel|
tools = persona.find_tools(partial, bot_user: user, llm: llm, context: context)
if (tools.present?)
tool_found = true
# a bit hacky, but extra newlines do no harm
if needs_newlines
update_blk.call("\n\n", cancel, nil)
needs_newlines = false
end
tools[0..MAX_TOOLS].each do |tool|
process_tool(tool, raw_context, llm, cancel, update_blk, prompt, context)
ongoing_chain &&= tool.chain_next_response?
end
else
needs_newlines = true
update_blk.call(partial, cancel, nil)
end
end
if !tool_found
ongoing_chain = false
raw_context << [result, bot_user.username]
end
total_completions += 1
# do not allow tools when we are at the end of a chain (total_completions == MAX_COMPLETIONS)
prompt.tools = [] if total_completions == MAX_COMPLETIONS
end
raw_context
end
private
def process_tool(tool, raw_context, llm, cancel, update_blk, prompt, context)
tool_call_id = tool.tool_call_id
invocation_result_json = invoke_tool(tool, llm, cancel, context, &update_blk).to_json
tool_call_message = {
type: :tool_call,
id: tool_call_id,
content: { arguments: tool.parameters }.to_json,
name: tool.name,
}
tool_message = {
type: :tool,
id: tool_call_id,
content: invocation_result_json,
name: tool.name,
}
if tool.standalone?
standalone_context =
context.dup.merge(
conversation_context: [
context[:conversation_context].last,
tool_call_message,
tool_message,
],
)
prompt = persona.craft_prompt(standalone_context)
else
prompt.push(**tool_call_message)
prompt.push(**tool_message)
end
raw_context << [tool_call_message[:content], tool_call_id, "tool_call", tool.name]
raw_context << [invocation_result_json, tool_call_id, "tool", tool.name]
end
def invoke_tool(tool, llm, cancel, context, &update_blk)
update_blk.call("", cancel, build_placeholder(tool.summary, ""))
result =
tool.invoke do |progress|
placeholder = build_placeholder(tool.summary, progress)
update_blk.call("", cancel, placeholder)
end
tool_details = build_placeholder(tool.summary, tool.details, custom_raw: tool.custom_raw)
if context[:skip_tool_details] && tool.custom_raw.present?
update_blk.call(tool.custom_raw, cancel, nil)
elsif !context[:skip_tool_details]
update_blk.call(tool_details, cancel, nil)
end
result
end
def self.guess_model(bot_user)
associated_llm = LlmModel.find_by(user_id: bot_user.id)
return if associated_llm.nil? # Might be a persona user. Handled by constructor.
"custom:#{associated_llm.id}"
end
def build_placeholder(summary, details, custom_raw: nil)
placeholder = +(<<~HTML)
<details>
<summary>#{summary}</summary>
<p>#{details}</p>
</details>
HTML
if custom_raw
placeholder << "\n"
placeholder << custom_raw
else
# we need this for cursor placeholder to work
# doing this in CSS is very hard
# if changing test with a custom tool such as search
placeholder << "<span></span>\n\n"
end
placeholder
end
end
end
end