FEATURE: Multi-model support for the AI Bot module. (#56)

We'll create one bot user for each available model. When listed in the `ai_bot_enabled_chat_bots` setting, they will reply.

This PR lets us use Claude-v1 in stream mode.
This commit is contained in:
Roman Rizzi 2023-05-11 10:03:03 -03:00 committed by GitHub
parent e5537d4c77
commit 7e3cb0ea16
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20 changed files with 670 additions and 246 deletions

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@ -3,5 +3,21 @@
class AiApiAuditLog < ActiveRecord::Base
module Provider
OpenAI = 1
Anthropic = 2
end
end
# == Schema Information
#
# Table name: ai_api_audit_logs
#
# id :bigint not null, primary key
# provider_id :integer not null
# user_id :integer
# request_tokens :integer
# response_tokens :integer
# raw_request_payload :string
# raw_response_payload :string
# created_at :datetime not null
# updated_at :datetime not null
#

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@ -4,52 +4,11 @@ class CompletionPrompt < ActiveRecord::Base
# TODO(roman): Remove sept 2023.
self.ignored_columns = ["value"]
# GPT 3.5 allows 4000 tokens
MAX_PROMPT_TOKENS = 3500
enum :prompt_type, { text: 0, list: 1, diff: 2 }
validates :messages, length: { maximum: 20 }
validate :each_message_length
def self.bot_prompt_with_topic_context(post)
messages = []
conversation =
post
.topic
.posts
.includes(:user)
.where("post_number <= ?", post.post_number)
.order("post_number desc")
.pluck(:raw, :username)
total_prompt_tokens = 0
messages =
conversation.reduce([]) do |memo, (raw, username)|
break(memo) if total_prompt_tokens >= MAX_PROMPT_TOKENS
tokens = DiscourseAi::Tokenizer.tokenize(raw)
if tokens.length + total_prompt_tokens > MAX_PROMPT_TOKENS
tokens = tokens[0...(MAX_PROMPT_TOKENS - total_prompt_tokens)]
raw = tokens.join(" ")
end
total_prompt_tokens += tokens.length
role = username == Discourse.gpt_bot.username ? "system" : "user"
memo.unshift({ role: role, content: raw })
end
messages.unshift({ role: "system", content: <<~TEXT })
You are gpt-bot. You answer questions and generate text.
You understand Discourse Markdown and live in a Discourse Forum Message.
You are provided you with context of previous discussions.
TEXT
messages
end
def messages_with_user_input(user_input)
if ::DiscourseAi::AiHelper::LlmPrompt.new.enabled_provider == "openai"
self.messages << { role: "user", content: user_input }

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@ -5,7 +5,7 @@ import { popupAjaxError } from "discourse/lib/ajax-error";
import loadScript from "discourse/lib/load-script";
function isGPTBot(user) {
return user && user.id === -110;
return user && [-110, -111, -112].includes(user.id);
}
function initializeAIBotReplies(api) {
@ -74,7 +74,7 @@ function initializeAIBotReplies(api) {
if (
this.model.isPrivateMessage &&
this.model.details.allowed_users &&
this.model.details.allowed_users.filter(isGPTBot).length === 1
this.model.details.allowed_users.filter(isGPTBot).length >= 1
) {
this.messageBus.subscribe(
`discourse-ai/ai-bot/topic/${this.model.id}`,
@ -83,7 +83,7 @@ function initializeAIBotReplies(api) {
}
},
unsubscribe: function () {
this.messageBus.unsubscribe("discourse-ai/ai-bot/topic/");
this.messageBus.unsubscribe("discourse-ai/ai-bot/topic/*");
this._super();
},
});

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@ -32,6 +32,7 @@ en:
ai_nsfw_models: "Models to use for NSFW inference."
ai_openai_api_key: "API key for OpenAI API"
ai_anthropic_api_key: "API key for Anthropic API"
composer_ai_helper_enabled: "Enable the Composer's AI helper."
ai_helper_allowed_groups: "Users on these groups will see the AI helper button in the composer."
@ -58,6 +59,7 @@ en:
ai_bot_enabled: "Enable the AI Bot module."
ai_bot_allowed_groups: "When the GPT Bot has access to the PM, it will reply to members of these groups."
ai_bot_enabled_chat_bots: "Available models to act as an AI Bot"
reviewables:

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@ -179,4 +179,13 @@ plugins:
client: true
type: group_list
list_type: compact
default: "3|14" # 3: @staff, 14: @trust_level_4
default: "3|14" # 3: @staff, 14: @trust_level_4
# Adding a new bot? Make sure to create a user for it on the seed file.
ai_bot_enabled_chat_bots:
type: list
default: "gpt-3.5-turbo"
client: true
choices:
- gpt-3.5-turbo
- gpt-4
- claude-v1

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@ -1,20 +1,22 @@
# frozen_string_literal: true
UserEmail.seed do |ue|
ue.id = -110
ue.email = "no_email_gpt_bot"
ue.primary = true
ue.user_id = -110
end
DiscourseAi::AiBot::EntryPoint::BOTS.each do |id, bot_username|
UserEmail.seed do |ue|
ue.id = id
ue.email = "no_email_#{bot_username}"
ue.primary = true
ue.user_id = id
end
User.seed do |u|
u.id = -110
u.name = "GPT Bot"
u.username = UserNameSuggester.suggest("gpt_bot")
u.password = SecureRandom.hex
u.active = true
u.admin = true
u.moderator = true
u.approved = true
u.trust_level = TrustLevel[4]
User.seed do |u|
u.id = id
u.name = bot_username.titleize
u.username = UserNameSuggester.suggest(bot_username)
u.password = SecureRandom.hex
u.active = true
u.admin = true
u.moderator = true
u.approved = true
u.trust_level = TrustLevel[4]
end
end

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@ -0,0 +1,45 @@
# frozen_string_literal: true
module DiscourseAi
module AiBot
class AnthropicBot < Bot
def self.can_reply_as?(bot_user)
bot_user.id == DiscourseAi::AiBot::EntryPoint::CLAUDE_V1_ID
end
def bot_prompt_with_topic_context(post)
super(post).join("\n\n")
end
def prompt_limit
7500 # https://console.anthropic.com/docs/prompt-design#what-is-a-prompt
end
private
def build_message(poster_username, content)
role = poster_username == bot_user.username ? "Assistant" : "Human"
"#{role}: #{content}"
end
def model_for
"claude-v1"
end
def update_with_delta(_, partial)
partial[:completion]
end
def submit_prompt_and_stream_reply(prompt, &blk)
DiscourseAi::Inference::AnthropicCompletions.perform!(
prompt,
model_for,
temperature: 0.4,
max_tokens: 3000,
&blk
)
end
end
end
end

144
lib/modules/ai_bot/bot.rb Normal file
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@ -0,0 +1,144 @@
# frozen_string_literal: true
module DiscourseAi
module AiBot
class Bot
BOT_NOT_FOUND = Class.new(StandardError)
def self.as(bot_user)
available_bots = [DiscourseAi::AiBot::OpenAiBot, DiscourseAi::AiBot::AnthropicBot]
bot =
available_bots.detect(-> { raise BOT_NOT_FOUND }) do |bot_klass|
bot_klass.can_reply_as?(bot_user)
end
bot.new(bot_user)
end
def initialize(bot_user)
@bot_user = bot_user
end
def reply_to(post)
prompt = bot_prompt_with_topic_context(post)
redis_stream_key = nil
reply = +""
bot_reply_post = nil
start = Time.now
submit_prompt_and_stream_reply(prompt) do |partial, cancel|
reply = update_with_delta(reply, partial)
if redis_stream_key && !Discourse.redis.get(redis_stream_key)
cancel&.call
bot_reply_post.update!(raw: reply, cooked: PrettyText.cook(reply)) if bot_reply_post
end
next if reply.length < SiteSetting.min_personal_message_post_length
# Minor hack to skip the delay during tests.
next if (Time.now - start < 0.5) && !Rails.env.test?
if bot_reply_post
Discourse.redis.expire(redis_stream_key, 60)
start = Time.now
publish_update(bot_reply_post, raw: reply.dup)
else
bot_reply_post =
PostCreator.create!(
bot_user,
topic_id: post.topic_id,
raw: reply,
skip_validations: false,
)
redis_stream_key = "gpt_cancel:#{bot_reply_post.id}"
Discourse.redis.setex(redis_stream_key, 60, 1)
end
end
if bot_reply_post
publish_update(bot_reply_post, done: true)
bot_reply_post.revise(
bot_user,
{ raw: reply },
skip_validations: true,
skip_revision: true,
)
end
rescue => e
Discourse.warn_exception(e, message: "ai-bot: Reply failed")
end
def bot_prompt_with_topic_context(post)
messages = []
conversation = conversation_context(post)
total_prompt_tokens = 0
messages =
conversation.reduce([]) do |memo, (raw, username)|
break(memo) if total_prompt_tokens >= prompt_limit
tokens = DiscourseAi::Tokenizer.tokenize(raw)
if tokens.length + total_prompt_tokens > prompt_limit
tokens = tokens[0...(prompt_limit - total_prompt_tokens)]
raw = tokens.join(" ")
end
total_prompt_tokens += tokens.length
memo.unshift(build_message(username, raw))
end
messages.unshift(build_message(bot_user.username, <<~TEXT))
You are gpt-bot. You answer questions and generate text.
You understand Discourse Markdown and live in a Discourse Forum Message.
You are provided you with context of previous discussions.
TEXT
messages
end
def prompt_limit
raise NotImplemented
end
protected
attr_reader :bot_user
def model_for(bot)
raise NotImplemented
end
def get_delta_from(partial)
raise NotImplemented
end
def submit_prompt_and_stream_reply(prompt, &blk)
raise NotImplemented
end
def conversation_context(post)
post
.topic
.posts
.includes(:user)
.where("post_number <= ?", post.post_number)
.order("post_number desc")
.pluck(:raw, :username)
end
def publish_update(bot_reply_post, payload)
MessageBus.publish(
"discourse-ai/ai-bot/topic/#{bot_reply_post.topic_id}",
payload.merge(post_id: bot_reply_post.id, post_number: bot_reply_post.post_number),
user_ids: bot_reply_post.topic.allowed_user_ids,
)
end
end
end
end

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@ -3,10 +3,20 @@
module DiscourseAi
module AiBot
class EntryPoint
AI_BOT_ID = -110
GPT4_ID = -110
GPT3_5_TURBO_ID = -111
CLAUDE_V1_ID = -112
BOTS = [
[GPT4_ID, "gpt4_bot"],
[GPT3_5_TURBO_ID, "gpt3.5_bot"],
[CLAUDE_V1_ID, "claude_v1_bot"],
]
def load_files
require_relative "jobs/regular/create_ai_reply"
require_relative "bot"
require_relative "anthropic_bot"
require_relative "open_ai_bot"
end
def inject_into(plugin)
@ -14,21 +24,15 @@ module DiscourseAi
Rails.root.join("plugins", "discourse-ai", "db", "fixtures", "ai_bot"),
)
plugin.add_class_method(Discourse, :gpt_bot) do
@ai_bots ||= {}
current_db = RailsMultisite::ConnectionManagement.current_db
@ai_bots[current_db] ||= User.find(AI_BOT_ID)
end
plugin.on(:post_created) do |post|
if post.topic.private_message? && post.user_id != AI_BOT_ID &&
post.topic.topic_allowed_users.exists?(user_id: Discourse.gpt_bot.id)
in_allowed_group =
SiteSetting.ai_bot_allowed_groups_map.any? do |group_id|
post.user.group_ids.include?(group_id)
end
bot_ids = BOTS.map(&:first)
Jobs.enqueue(:create_ai_reply, post_id: post.id) if in_allowed_group
if post.topic.private_message? && !bot_ids.include?(post.user_id)
if (SiteSetting.ai_bot_allowed_groups_map & post.user.group_ids).present?
bot_id = post.topic.topic_allowed_users.where(user_id: bot_ids).first&.user_id
Jobs.enqueue(:create_ai_reply, post_id: post.id, bot_user_id: bot_id) if bot_id
end
end
end
end

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@ -5,72 +5,11 @@ module ::Jobs
sidekiq_options retry: false
def execute(args)
return unless bot_user = User.find_by(id: args[:bot_user_id])
return unless bot = DiscourseAi::AiBot::Bot.as(bot_user)
return unless post = Post.includes(:topic).find_by(id: args[:post_id])
prompt = CompletionPrompt.bot_prompt_with_topic_context(post)
redis_stream_key = nil
reply = +""
bot_reply_post = nil
start = Time.now
DiscourseAi::Inference::OpenAiCompletions.perform!(
prompt,
temperature: 0.4,
top_p: 0.9,
max_tokens: 3000,
) do |partial, cancel|
content_delta = partial.dig(:choices, 0, :delta, :content)
reply << content_delta if content_delta
if redis_stream_key && !Discourse.redis.get(redis_stream_key)
cancel&.call
bot_reply_post.update!(raw: reply, cooked: PrettyText.cook(reply)) if bot_reply_post
end
next if reply.length < SiteSetting.min_personal_message_post_length
# Minor hack to skip the delay during tests.
next if (Time.now - start < 0.5) && !Rails.env.test?
if bot_reply_post
Discourse.redis.expire(redis_stream_key, 60)
start = Time.now
MessageBus.publish(
"discourse-ai/ai-bot/topic/#{post.topic_id}",
{ raw: reply.dup, post_id: bot_reply_post.id, post_number: bot_reply_post.post_number },
user_ids: post.topic.allowed_user_ids,
)
else
bot_reply_post =
PostCreator.create!(
Discourse.gpt_bot,
topic_id: post.topic_id,
raw: reply,
skip_validations: false,
)
redis_stream_key = "gpt_cancel:#{bot_reply_post.id}"
Discourse.redis.setex(redis_stream_key, 60, 1)
end
end
MessageBus.publish(
"discourse-ai/ai-bot/topic/#{post.topic_id}",
{ done: true, post_id: bot_reply_post.id, post_number: bot_reply_post.post_number },
user_ids: post.topic.allowed_user_ids,
)
if bot_reply_post
bot_reply_post.revise(
Discourse.gpt_bot,
{ raw: reply },
skip_validations: true,
skip_revision: true,
)
end
rescue => e
Discourse.warn_exception(e, message: "ai-bot: Reply failed")
bot.reply_to(post)
end
end
end

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@ -0,0 +1,48 @@
# frozen_string_literal: true
module DiscourseAi
module AiBot
class OpenAiBot < Bot
def self.can_reply_as?(bot_user)
open_ai_bot_ids = [
DiscourseAi::AiBot::EntryPoint::GPT4_ID,
DiscourseAi::AiBot::EntryPoint::GPT3_5_TURBO_ID,
]
open_ai_bot_ids.include?(bot_user.id)
end
def prompt_limit
3500
end
private
def build_message(poster_username, content)
role = poster_username == bot_user.username ? "system" : "user"
{ role: role, content: content }
end
def model_for
return "gpt-4" if bot_user.id == DiscourseAi::AiBot::EntryPoint::GPT4_ID
"gpt-3.5-turbo"
end
def update_with_delta(current_delta, partial)
current_delta + partial.dig(:choices, 0, :delta, :content).to_s
end
def submit_prompt_and_stream_reply(prompt, &blk)
DiscourseAi::Inference::OpenAiCompletions.perform!(
prompt,
model_for,
temperature: 0.4,
top_p: 0.9,
max_tokens: 3000,
&blk
)
end
end
end
end

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@ -64,7 +64,7 @@ module DiscourseAi
messages = prompt.messages_with_user_input(text)
result[:suggestions] = DiscourseAi::Inference::OpenAiCompletions
.perform!(messages)
.perform!(messages, SiteSetting.ai_helper_model)
.dig(:choices)
.to_a
.flat_map { |choice| parse_content(prompt, choice.dig(:message, :content).to_s) }

View File

@ -4,32 +4,106 @@ module ::DiscourseAi
module Inference
class AnthropicCompletions
CompletionFailed = Class.new(StandardError)
TIMEOUT = 60
def self.perform!(prompt)
def self.perform!(
prompt,
model = "claude-v1",
temperature: nil,
top_p: nil,
max_tokens: nil,
user_id: nil
)
url = URI("https://api.anthropic.com/v1/complete")
headers = {
"x-api-key" => SiteSetting.ai_anthropic_api_key,
"Content-Type" => "application/json",
}
model = "claude-v1"
payload = { model: model, prompt: prompt }
connection_opts = { request: { write_timeout: 60, read_timeout: 60, open_timeout: 60 } }
payload[:temperature] = temperature if temperature
payload[:top_p] = top_p if top_p
payload[:max_tokens_to_sample] = max_tokens || 300
payload[:stream] = true if block_given?
response =
Faraday.new(nil, connection_opts).post(
"https://api.anthropic.com/v1/complete",
{ model: model, prompt: prompt, max_tokens_to_sample: 300 }.to_json,
headers,
)
Net::HTTP.start(
url.host,
url.port,
use_ssl: true,
read_timeout: TIMEOUT,
open_timeout: TIMEOUT,
write_timeout: TIMEOUT,
) do |http|
request = Net::HTTP::Post.new(url, headers)
request_body = payload.to_json
request.body = request_body
if response.status != 200
Rails.logger.error(
"AnthropicCompletions: status: #{response.status} - body: #{response.body}",
)
raise CompletionFailed
http.request(request) do |response|
if response.code.to_i != 200
Rails.logger.error(
"AnthropicCompletions: status: #{response.code.to_i} - body: #{response.body}",
)
raise CompletionFailed
end
log =
AiApiAuditLog.create!(
provider_id: AiApiAuditLog::Provider::Anthropic,
raw_request_payload: request_body,
user_id: user_id,
)
if !block_given?
response_body = response.read_body
parsed_response = JSON.parse(response_body, symbolize_names: true)
log.update!(
raw_response_payload: response_body,
request_tokens: DiscourseAi::Tokenizer.size(prompt),
response_tokens: DiscourseAi::Tokenizer.size(parsed_response[:completion]),
)
return parsed_response
end
begin
cancelled = false
cancel = lambda { cancelled = true }
response_data = +""
response_raw = +""
response.read_body do |chunk|
if cancelled
http.finish
return
end
response_raw << chunk
chunk
.split("\n")
.each do |line|
data = line.split("data: ", 2)[1]
next if !data || data.squish == "[DONE]"
if !cancelled && partial = JSON.parse(data, symbolize_names: true)
response_data << partial[:completion].to_s
yield partial, cancel
end
end
rescue IOError
raise if !cancelled
ensure
log.update!(
raw_response_payload: response_raw,
request_tokens: DiscourseAi::Tokenizer.size(prompt),
response_tokens: DiscourseAi::Tokenizer.size(response_data),
)
end
end
end
end
JSON.parse(response.body, symbolize_names: true)
end
end
end

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@ -9,7 +9,7 @@ module ::DiscourseAi
def self.perform!(
messages,
model = SiteSetting.ai_helper_model,
model,
temperature: nil,
top_p: nil,
max_tokens: nil,

View File

@ -4,7 +4,7 @@ RSpec.describe DiscourseAi::AiBot::EntryPoint do
describe "#inject_into" do
describe "subscribes to the post_created event" do
fab!(:admin) { Fabricate(:admin) }
let(:gpt_bot) { Discourse.gpt_bot }
let(:gpt_bot) { User.find(described_class::GPT4_ID) }
fab!(:bot_allowed_group) { Fabricate(:group) }
let(:post_args) do
@ -13,7 +13,6 @@ RSpec.describe DiscourseAi::AiBot::EntryPoint do
raw: "Hello, Can you please tell me a story?",
archetype: Archetype.private_message,
target_usernames: [gpt_bot.username].join(","),
category: 1,
}
end
@ -29,6 +28,19 @@ RSpec.describe DiscourseAi::AiBot::EntryPoint do
).by(1)
end
it "includes the bot's user_id" do
claude_bot = User.find(described_class::CLAUDE_V1_ID)
claude_post_attrs = post_args.merge(target_usernames: [claude_bot.username].join(","))
expect { PostCreator.create!(admin, claude_post_attrs) }.to change(
Jobs::CreateAiReply.jobs,
:size,
).by(1)
job_args = Jobs::CreateAiReply.jobs.last["args"].first
expect(job_args["bot_user_id"]).to eq(claude_bot.id)
end
context "when the post is not from a PM" do
it "does nothing" do
expect {

View File

@ -1,6 +1,7 @@
# frozen_string_literal: true
require_relative "../../../../../support/openai_completions_inference_stubs"
require_relative "../../../../../support/anthropic_completion_stubs"
RSpec.describe Jobs::CreateAiReply do
describe "#execute" do
@ -10,44 +11,82 @@ RSpec.describe Jobs::CreateAiReply do
let(:expected_response) do
"Hello this is a bot and what you just said is an interesting question"
end
let(:deltas) { expected_response.split(" ").map { |w| { content: "#{w} " } } }
before do
SiteSetting.min_personal_message_post_length = 5
before { SiteSetting.min_personal_message_post_length = 5 }
OpenAiCompletionsInferenceStubs.stub_streamed_response(
CompletionPrompt.bot_prompt_with_topic_context(post),
deltas,
req_opts: {
temperature: 0.4,
top_p: 0.9,
max_tokens: 3000,
stream: true,
},
)
end
context "when chatting with the Open AI bot" do
let(:deltas) { expected_response.split(" ").map { |w| { content: "#{w} " } } }
it "adds a reply from the GPT bot" do
subject.execute(post_id: topic.first_post.id)
before do
bot_user = User.find(DiscourseAi::AiBot::EntryPoint::GPT3_5_TURBO_ID)
expect(topic.posts.last.raw).to eq(expected_response)
end
it "streams the reply on the fly to the client through MB" do
messages =
MessageBus.track_publish("discourse-ai/ai-bot/topic/#{topic.id}") do
subject.execute(post_id: topic.first_post.id)
end
done_signal = messages.pop
expect(messages.length).to eq(deltas.length)
messages.each_with_index do |m, idx|
expect(m.data[:raw]).to eq(deltas[0..(idx + 1)].map { |d| d[:content] }.join)
OpenAiCompletionsInferenceStubs.stub_streamed_response(
DiscourseAi::AiBot::OpenAiBot.new(bot_user).bot_prompt_with_topic_context(post),
deltas,
req_opts: {
temperature: 0.4,
top_p: 0.9,
max_tokens: 3000,
stream: true,
},
)
end
expect(done_signal.data[:done]).to eq(true)
it "adds a reply from the GPT bot" do
subject.execute(
post_id: topic.first_post.id,
bot_user_id: DiscourseAi::AiBot::EntryPoint::GPT3_5_TURBO_ID,
)
expect(topic.posts.last.raw).to eq(expected_response)
end
it "streams the reply on the fly to the client through MB" do
messages =
MessageBus.track_publish("discourse-ai/ai-bot/topic/#{topic.id}") do
subject.execute(
post_id: topic.first_post.id,
bot_user_id: DiscourseAi::AiBot::EntryPoint::GPT3_5_TURBO_ID,
)
end
done_signal = messages.pop
expect(messages.length).to eq(deltas.length)
messages.each_with_index do |m, idx|
expect(m.data[:raw]).to eq(deltas[0..(idx + 1)].map { |d| d[:content] }.join)
end
expect(done_signal.data[:done]).to eq(true)
end
end
context "when chatting with Claude from Anthropic" do
let(:deltas) { expected_response.split(" ").map { |w| "#{w} " } }
before do
bot_user = User.find(DiscourseAi::AiBot::EntryPoint::CLAUDE_V1_ID)
AnthropicCompletionStubs.stub_streamed_response(
DiscourseAi::AiBot::AnthropicBot.new(bot_user).bot_prompt_with_topic_context(post),
deltas,
req_opts: {
temperature: 0.4,
max_tokens_to_sample: 3000,
stream: true,
},
)
end
it "adds a reply from the Claude bot" do
subject.execute(
post_id: topic.first_post.id,
bot_user_id: DiscourseAi::AiBot::EntryPoint::CLAUDE_V1_ID,
)
expect(topic.posts.last.raw).to eq(expected_response)
end
end
end
end

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@ -0,0 +1,64 @@
# frozen_string_literal: true
RSpec.describe DiscourseAi::AiBot::OpenAiBot do
describe "#bot_prompt_with_topic_context" do
fab!(:topic) { Fabricate(:topic) }
def post_body(post_number)
"This is post #{post_number}"
end
def bot_user
User.find(DiscourseAi::AiBot::EntryPoint::GPT4_ID)
end
subject { described_class.new(bot_user) }
context "when the topic has one post" do
fab!(:post_1) { Fabricate(:post, topic: topic, raw: post_body(1), post_number: 1) }
it "includes it in the prompt" do
prompt_messages = subject.bot_prompt_with_topic_context(post_1)
post_1_message = prompt_messages[1]
expect(post_1_message[:role]).to eq("user")
expect(post_1_message[:content]).to eq(post_body(1))
end
end
context "when prompt gets very long" do
fab!(:post_1) { Fabricate(:post, topic: topic, raw: "test " * 6000, post_number: 1) }
it "trims the prompt" do
prompt_messages = subject.bot_prompt_with_topic_context(post_1)
expect(prompt_messages[0][:role]).to eq("system")
expect(prompt_messages[1][:role]).to eq("user")
expected_length = ("test " * (subject.prompt_limit)).length
expect(prompt_messages[1][:content].length).to eq(expected_length)
end
end
context "when the topic has multiple posts" do
fab!(:post_1) { Fabricate(:post, topic: topic, raw: post_body(1), post_number: 1) }
fab!(:post_2) do
Fabricate(:post, topic: topic, user: bot_user, raw: post_body(2), post_number: 2)
end
fab!(:post_3) { Fabricate(:post, topic: topic, raw: post_body(3), post_number: 3) }
it "includes them in the prompt respecting the post number order" do
prompt_messages = subject.bot_prompt_with_topic_context(post_3)
expect(prompt_messages[1][:role]).to eq("user")
expect(prompt_messages[1][:content]).to eq(post_body(1))
expect(prompt_messages[2][:role]).to eq("system")
expect(prompt_messages[2][:content]).to eq(post_body(2))
expect(prompt_messages[3][:role]).to eq("user")
expect(prompt_messages[3][:content]).to eq(post_body(3))
end
end
end
end

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@ -18,59 +18,4 @@ RSpec.describe CompletionPrompt do
end
end
end
describe ".bot_prompt_with_topic_context" do
fab!(:topic) { Fabricate(:topic) }
def post_body(post_number)
"This is post #{post_number}"
end
context "when the topic has one post" do
fab!(:post_1) { Fabricate(:post, topic: topic, raw: post_body(1), post_number: 1) }
it "includes it in the prompt" do
prompt_messages = described_class.bot_prompt_with_topic_context(post_1)
post_1_message = prompt_messages[1]
expect(post_1_message[:role]).to eq("user")
expect(post_1_message[:content]).to eq(post_body(1))
end
end
context "when prompt gets very long" do
fab!(:post_1) { Fabricate(:post, topic: topic, raw: "test " * 6000, post_number: 1) }
it "trims the prompt" do
prompt_messages = described_class.bot_prompt_with_topic_context(post_1)
expect(prompt_messages[0][:role]).to eq("system")
expect(prompt_messages[1][:role]).to eq("user")
expected_length = ("test " * (CompletionPrompt::MAX_PROMPT_TOKENS)).length
expect(prompt_messages[1][:content].length).to eq(expected_length)
end
end
context "when the topic has multiple posts" do
fab!(:post_1) { Fabricate(:post, topic: topic, raw: post_body(1), post_number: 1) }
fab!(:post_2) do
Fabricate(:post, topic: topic, user: Discourse.gpt_bot, raw: post_body(2), post_number: 2)
end
fab!(:post_3) { Fabricate(:post, topic: topic, raw: post_body(3), post_number: 3) }
it "includes them in the prompt respecting the post number order" do
prompt_messages = described_class.bot_prompt_with_topic_context(post_3)
expect(prompt_messages[1][:role]).to eq("user")
expect(prompt_messages[1][:content]).to eq(post_body(1))
expect(prompt_messages[2][:role]).to eq("system")
expect(prompt_messages[2][:content]).to eq(post_body(2))
expect(prompt_messages[3][:role]).to eq("user")
expect(prompt_messages[3][:content]).to eq(post_body(3))
end
end
end
end

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# frozen_string_literal: true
require_relative "../../support/anthropic_completion_stubs"
RSpec.describe DiscourseAi::Inference::AnthropicCompletions do
before { SiteSetting.ai_anthropic_api_key = "abc-123" }
it "can complete a trivial prompt" do
response_text = "1. Serenity\\n2. Laughter\\n3. Adventure"
prompt = "Human: write 3 words\n\n"
user_id = 183
req_opts = { temperature: 0.5, max_tokens_to_sample: 700 }
AnthropicCompletionStubs.stub_response(prompt, response_text, req_opts: req_opts)
completions =
DiscourseAi::Inference::AnthropicCompletions.perform!(
prompt,
"claude-v1",
temperature: req_opts[:temperature],
max_tokens: req_opts[:max_tokens_to_sample],
user_id: user_id,
)
expect(completions[:completion]).to eq(response_text)
expect(AiApiAuditLog.count).to eq(1)
log = AiApiAuditLog.first
request_body = { model: "claude-v1", prompt: prompt }.merge(req_opts).to_json
response_body = AnthropicCompletionStubs.response(response_text).to_json
expect(log.provider_id).to eq(AiApiAuditLog::Provider::Anthropic)
expect(log.request_tokens).to eq(7)
expect(log.response_tokens).to eq(16)
expect(log.raw_request_payload).to eq(request_body)
expect(log.raw_response_payload).to eq(response_body)
end
it "supports streaming mode" do
deltas = ["Mount", "ain", " ", "Tree ", "Frog"]
prompt = "Human: write 3 words\n\n"
req_opts = { max_tokens_to_sample: 300, stream: true }
content = +""
AnthropicCompletionStubs.stub_streamed_response(prompt, deltas, req_opts: req_opts)
DiscourseAi::Inference::AnthropicCompletions.perform!(prompt, "claude-v1") do |partial, cancel|
data = partial[:completion]
content = data if data
cancel.call if content.split(" ").length == 2
end
expect(content).to eq("Mountain Tree ")
expect(AiApiAuditLog.count).to eq(1)
log = AiApiAuditLog.first
request_body = { model: "claude-v1", prompt: prompt }.merge(req_opts).to_json
expect(log.provider_id).to eq(AiApiAuditLog::Provider::Anthropic)
expect(log.request_tokens).to eq(7)
expect(log.response_tokens).to eq(9)
expect(log.raw_request_payload).to eq(request_body)
expect(log.raw_response_payload).to be_present
end
end

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@ -0,0 +1,55 @@
# frozen_string_literal: true
class AnthropicCompletionStubs
class << self
def response(content)
{
completion: content,
stop: "\n\nHuman:",
stop_reason: "stop_sequence",
truncated: false,
log_id: "12dcc7feafbee4a394e0de9dffde3ac5",
model: "claude-v1",
exception: nil,
}
end
def stub_response(prompt, response_text, req_opts: {})
WebMock
.stub_request(:post, "https://api.anthropic.com/v1/complete")
.with(body: { model: "claude-v1", prompt: prompt }.merge(req_opts).to_json)
.to_return(status: 200, body: JSON.dump(response(response_text)))
end
def stream_line(delta, finish_reason: nil)
+"data: " << {
completion: delta,
stop: finish_reason ? "\n\nHuman:" : nil,
stop_reason: finish_reason,
truncated: false,
log_id: "12b029451c6d18094d868bc04ce83f63",
model: "claude-v1",
exception: nil,
}.to_json
end
def stub_streamed_response(prompt, deltas, req_opts: {})
chunks =
deltas.each_with_index.map do |_, index|
if index == (deltas.length - 1)
stream_line(deltas.join(""), finish_reason: "stop_sequence")
else
stream_line(deltas[0..index].join(""))
end
end
chunks << "[DONE]"
chunks = chunks.join("\n\n")
WebMock
.stub_request(:post, "https://api.anthropic.com/v1/complete")
.with(body: { model: "claude-v1", prompt: prompt }.merge(req_opts).to_json)
.to_return(status: 200, body: chunks)
end
end
end