Files
discourse-ai/lib/ai_bot/bot.rb
T
Sam a48acc894a FEATURE: more accurate and faster titles (#791)
Previously we waited 1 minute before automatically titling PMs

The new change introduces adding a title immediately after the the
llm replies

Prompt was also modified to include the LLM reply in title suggestion.

This helps situation like:

user: tell me a joke
llm: a very funy joke about horses

Then the title would be "A Funny Horse Joke"

Specs already covered some auto title logic, amended to also
catch the new message bus message we have been sending.
2024-09-03 15:52:20 +10:00

214 lines
6.4 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 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
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