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feat(nx-dev): move all the querying logic to edge function (#18834)

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Katerina Skroumpelou 2023-08-31 16:49:33 +03:00 committed by GitHub
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11
nx-dev/data-access-ai/README.md
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@ -1,11 +0,0 @@
# nx-dev-data-access-ai
This library was generated with [Nx](https://nx.dev).
## Building
Run `nx build nx-dev-data-access-ai` to build the library.
## Running unit tests
Run `nx test nx-dev-data-access-ai` to execute the unit tests via [Jest](https://jestjs.io).

5
nx-dev/data-access-ai/package.json
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{
"name": "@nx/nx-dev/data-access-ai",
"version": "0.0.1",
"type": "commonjs"
}

2
nx-dev/data-access-ai/src/index.ts
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@ -1,2 +0,0 @@
export * from './lib/data-access-ai';
export * from './lib/utils';

265
nx-dev/data-access-ai/src/lib/data-access-ai.ts
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@ -1,265 +0,0 @@
// based on:
// https://github.com/supabase-community/nextjs-openai-doc-search/blob/main/pages/api/vector-search.ts
import {
PostgrestSingleResponse,
SupabaseClient,
createClient,
} from '@supabase/supabase-js';
import GPT3Tokenizer from 'gpt3-tokenizer';
import { CreateEmbeddingResponse, CreateCompletionResponseUsage } from 'openai';
import {
ApplicationError,
ChatItem,
PageSection,
UserError,
checkEnvVariables,
getListOfSources,
getMessageFromResponse,
initializeChat,
openAiCall,
sanitizeLinksInResponse,
toMarkdownList,
} from './utils';
const DEFAULT_MATCH_THRESHOLD = 0.78;
const DEFAULT_MATCH_COUNT = 15;
const MIN_CONTENT_LENGTH = 50;
// This limits history to 30 messages back and forth
// It's arbitrary, but also generous
// History length should be based on token count
// This is a temporary solution
const MAX_HISTORY_LENGTH = 30;
const supabaseUrl = process.env['NX_NEXT_PUBLIC_SUPABASE_URL'];
const supabaseServiceKey = process.env['NX_SUPABASE_SERVICE_ROLE_KEY'];
let chatFullHistory: ChatItem[] = [];
let totalTokensSoFar = 0;
let supabaseClient: SupabaseClient<any, 'public', any>;
export async function queryAi(
query: string,
aiResponse?: string
): Promise<{
textResponse: string;
usage?: CreateCompletionResponseUsage;
sources: { heading: string; url: string }[];
sourcesMarkdown: string;
}> {
if (!supabaseClient) {
supabaseClient = createClient(
supabaseUrl as string,
supabaseServiceKey as string
);
}
if (chatFullHistory.length > MAX_HISTORY_LENGTH) {
chatFullHistory.slice(0, MAX_HISTORY_LENGTH - 4);
}
try {
checkEnvVariables(supabaseUrl, supabaseServiceKey);
if (!query) {
throw new UserError('Missing query in request data');
}
// Moderate the content to comply with OpenAI T&C
const sanitizedQuery = query.trim();
const moderationResponseObj = await openAiCall(
{ input: sanitizedQuery },
'moderation'
);
const moderationResponse = await moderationResponseObj.json();
const [results] = moderationResponse.results;
if (results.flagged) {
throw new UserError('Flagged content', {
flagged: true,
categories: results.categories,
});
}
// Create embedding from query
// NOTE: Here, we may or may not want to include the previous AI response
/**
* For retrieving relevant Nx documentation sections via embeddings, it's a design decision.
* Including the prior response might give more contextually relevant sections,
* but just sending the query might suffice for many cases.
*
* We can experiment with this.
*
* How the solution looks like with previous response:
*
* const embeddingResponse = await openAiCall(
* { input: sanitizedQuery + aiResponse },
* 'embedding'
* );
*
* This costs more tokens, so if we see costs skyrocket we remove it.
* As it says in the docs, it's a design decision, and it may or may not really improve results.
*/
const embeddingResponseObj = await openAiCall(
{ input: sanitizedQuery + aiResponse, model: 'text-embedding-ada-002' },
'embedding'
);
if (!embeddingResponseObj.ok) {
throw new ApplicationError('Failed to create embedding for question', {
data: embeddingResponseObj.status,
});
}
const embeddingResponse = await embeddingResponseObj.json();
const {
data: [{ embedding }],
}: CreateEmbeddingResponse = embeddingResponse;
const { error: matchError, data: pageSections } = await supabaseClient.rpc(
'match_page_sections_2',
{
embedding,
match_threshold: DEFAULT_MATCH_THRESHOLD,
match_count: DEFAULT_MATCH_COUNT,
min_content_length: MIN_CONTENT_LENGTH,
}
);
if (matchError) {
throw new ApplicationError('Failed to match page sections', matchError);
}
// Note: this is experimental. I think it should work
// mainly because we're testing previous response + query.
if (!pageSections || pageSections.length === 0) {
throw new UserError('No results found.', { no_results: true });
}
const tokenizer = new GPT3Tokenizer({ type: 'gpt3' });
let tokenCount = 0;
let contextText = '';
for (let i = 0; i < (pageSections as PageSection[]).length; i++) {
const pageSection: PageSection = pageSections[i];
const content = pageSection.content;
const encoded = tokenizer.encode(content);
tokenCount += encoded.text.length;
if (tokenCount >= 2500) {
break;
}
contextText += `${content.trim()}\n---\n`;
}
const prompt = `
${`
You are a knowledgeable Nx representative.
Your knowledge is based entirely on the official Nx Documentation.
You can answer queries using ONLY that information.
You cannot answer queries using your own knowledge or experience.
Answer in markdown format. Always give an example, answer as thoroughly as you can, and
always provide a link to relevant documentation
on the https://nx.dev website. All the links you find or post
that look like local or relative links, always prepend with "https://nx.dev".
Your answer should be in the form of a Markdown article
(including related code snippets if available), much like the
existing Nx documentation. Mark the titles and the subsections with the appropriate markdown syntax.
If you are unsure and cannot find an answer in the Nx Documentation, say
"Sorry, I don't know how to help with that. You can visit the [Nx documentation](https://nx.dev/getting-started/intro) for more info."
Remember, answer the question using ONLY the information provided in the Nx Documentation.
`
.replace(/\s+/g, ' ')
.trim()}
`;
const { chatMessages: chatGptMessages, chatHistory } = initializeChat(
chatFullHistory,
query,
contextText,
prompt,
aiResponse
);
chatFullHistory = chatHistory;
const responseObj = await openAiCall(
{
model: 'gpt-3.5-turbo-16k',
messages: chatGptMessages,
temperature: 0,
stream: false,
},
'chatCompletion'
);
if (!responseObj.ok) {
throw new ApplicationError('Failed to generate completion', {
data: responseObj.status,
});
}
const response = await responseObj.json();
// Message asking to double-check
const callout: string =
'{% callout type="warning" title="Always double-check!" %}The results may not be accurate, so please always double check with our documentation.{% /callout %}\n';
// Append the warning message asking to double-check!
const message = [callout, getMessageFromResponse(response)].join('');
const responseWithoutBadLinks = await sanitizeLinksInResponse(message);
const sources = getListOfSources(pageSections);
totalTokensSoFar += response.usage?.total_tokens ?? 0;
return {
textResponse: responseWithoutBadLinks,
usage: response.usage as CreateCompletionResponseUsage,
sources,
sourcesMarkdown: toMarkdownList(sources),
};
} catch (err: unknown) {
if (err instanceof UserError) {
console.error(err.message);
} else if (err instanceof ApplicationError) {
// Print out application errors with their additional data
console.error(`${err.message}: ${JSON.stringify(err.data)}`);
} else {
// Print out unexpected errors as is to help with debugging
console.error(err);
}
// TODO: include more response info in debug environments
console.error(err);
throw err;
}
}
export function resetHistory() {
chatFullHistory = [];
totalTokensSoFar = 0;
}
export function getHistory(): ChatItem[] {
return chatFullHistory;
}
export async function sendFeedbackAnalytics(feedback: {}): Promise<
PostgrestSingleResponse<null>
> {
return supabaseClient.from('feedback').insert(feedback);
}
export async function sendQueryAnalytics(queryInfo: {}) {
const { error } = await supabaseClient.from('user_queries').insert(queryInfo);
if (error) {
console.error('Error storing the query info in Supabase: ', error);
}
}

223
nx-dev/data-access-ai/src/lib/utils.ts
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@ -1,223 +0,0 @@
import {
ChatCompletionRequestMessageRoleEnum,
CreateChatCompletionResponse,
} from 'openai';
import { getHistory } from './data-access-ai';
export interface PageSection {
id: number;
page_id: number;
content: string;
heading: string;
similarity: number;
slug: string;
url_partial: string | null;
}
export function getMessageFromResponse(
response: CreateChatCompletionResponse
): string {
return response.choices[0].message?.content ?? '';
}
export function getListOfSources(
pageSections: PageSection[]
): { heading: string; url: string }[] {
const uniqueUrlPartials = new Set<string | null>();
const result = pageSections
.filter((section) => {
if (section.url_partial && !uniqueUrlPartials.has(section.url_partial)) {
uniqueUrlPartials.add(section.url_partial);
return true;
}
return false;
})
.map((section) => {
const url = new URL('https://nx.dev');
url.pathname = section.url_partial as string;
if (section.slug) {
url.hash = section.slug;
}
return {
heading: section.heading,
url: url.toString(),
};
});
return result;
}
export function toMarkdownList(
sections: { heading: string; url: string }[]
): string {
return sections
.map((section) => `- [${section.heading}](${section.url})`)
.join('\n');
}
export async function sanitizeLinksInResponse(
response: string
): Promise<string> {
const regex = /https:\/\/nx\.dev[^) \n]*[^).]/g;
const urls = response.match(regex);
if (urls) {
for (const url of urls) {
const linkIsWrong = await is404(url);
if (linkIsWrong) {
response = response.replace(
url,
'https://nx.dev/getting-started/intro'
);
}
}
}
return response;
}
async function is404(url: string): Promise<boolean> {
try {
const response = await fetch(url.replace('https://nx.dev', ''));
if (response.status === 404) {
return true;
} else {
return false;
}
} catch (error) {
if ((error as any)?.response?.status === 404) {
return true;
} else {
return false;
}
}
}
export function checkEnvVariables(
supabaseUrl?: string,
supabaseServiceKey?: string
) {
if (!supabaseUrl) {
throw new ApplicationError(
'Missing environment variable NX_NEXT_PUBLIC_SUPABASE_URL'
);
}
if (!supabaseServiceKey) {
throw new ApplicationError(
'Missing environment variable NX_SUPABASE_SERVICE_ROLE_KEY'
);
}
}
export class ApplicationError extends Error {
public type: string = 'application_error';
constructor(message: string, public data: Record<string, any> = {}) {
super(message);
}
}
export class UserError extends ApplicationError {
public override type: string = 'user_error';
constructor(message: string, data: Record<string, any> = {}) {
super(message, data);
}
}
/**
* Initializes a chat session by generating the initial chat messages based on the given parameters.
*
* @param {ChatItem[]} chatFullHistory - The full chat history.
* @param {string} query - The user's query.
* @param {string} contextText - The context text or Nx Documentation.
* @param {string} prompt - The prompt message displayed to the user.
* @param {string} [aiResponse] - The AI assistant's response.
* @returns {Object} - An object containing the generated chat messages and updated chat history.
* - chatMessages: An array of chat messages for the chat session.
* - chatHistory: The updated chat history.
*/
export function initializeChat(
chatFullHistory: ChatItem[],
query: string,
contextText: string,
prompt: string,
aiResponse?: string
): { chatMessages: ChatItem[]; chatHistory: ChatItem[] } {
const finalQuery = `
You will be provided the Nx Documentation.
Answer my message provided by following the approach below:
- Step 1: Identify CLUES (keywords, phrases, contextual information, references) in the input that you could use to generate an answer.
- Step 2: Deduce the diagnostic REASONING process from the premises (clues, question), relying ONLY on the information provided in the Nx Documentation. If you recognize vulgar language, answer the question if possible, and educate the user to stay polite.
- Step 3: EVALUATE the reasoning. If the reasoning aligns with the Nx Documentation, accept it. Do not use any external knowledge or make assumptions outside of the provided Nx documentation. If the reasoning doesn't strictly align with the Nx Documentation or relies on external knowledge or inference, reject it and answer with the exact string:
"Sorry, I don't know how to help with that. You can visit the [Nx documentation](https://nx.dev/getting-started/intro) for more info."
- Final Step: You can also rely on the messages we have exchanged so far. Do NOT reveal the approach to the user.
Nx Documentation:
${contextText}
---- My message: ${query}
`;
let chatGptMessages: ChatItem[] = [];
let messages: ChatItem[] = [];
if (chatFullHistory.length > 0) {
messages = [
{
role: ChatCompletionRequestMessageRoleEnum.Assistant,
content: aiResponse ?? '',
},
{ role: ChatCompletionRequestMessageRoleEnum.User, content: finalQuery },
];
chatGptMessages = [...chatFullHistory, ...messages];
} else {
messages = [
{ role: ChatCompletionRequestMessageRoleEnum.System, content: prompt },
{ role: ChatCompletionRequestMessageRoleEnum.User, content: finalQuery },
];
chatGptMessages = [...messages];
}
chatFullHistory.push(...messages);
return { chatMessages: chatGptMessages, chatHistory: chatFullHistory };
}
export function extractQuery(text: string) {
const regex = /---- My message: (.+)/;
const match = text.match(regex);
return match ? match[1].trim() : text;
}
export function getProcessedHistory(): ChatItem[] {
let history = getHistory();
history = history
.map((item) => {
if (item.role === ChatCompletionRequestMessageRoleEnum.User) {
item.content = extractQuery(item.content);
}
if (item.role !== ChatCompletionRequestMessageRoleEnum.System) {
return item;
} else {
return undefined;
}
})
.filter((item) => !!item) as ChatItem[];
return history;
}
export interface ChatItem {
role: ChatCompletionRequestMessageRoleEnum;
content: string;
}
export function openAiCall(
input: object,
action: 'moderation' | 'embedding' | 'chatCompletion'
) {
return fetch('/api/openai-handler', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
action,
input: { ...input },
}),
});
}

9
nx-dev/feature-ai/src/lib/error-message.tsx
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@ -4,7 +4,14 @@ import {
} from '@heroicons/react/24/outline'; } from '@heroicons/react/24/outline';
export function ErrorMessage({ error }: { error: any }): JSX.Element { export function ErrorMessage({ error }: { error: any }): JSX.Element {
if (error.data.no_results) { try {
if (error.message) {
error = JSON.parse(error.message);
console.error('Error: ', error);
}
} catch (e) {}
if (error?.data?.no_results) {
return ( return (
<div className="rounded-md bg-yellow-50 p-4"> <div className="rounded-md bg-yellow-50 p-4">
<div className="flex"> <div className="flex">

135
nx-dev/feature-ai/src/lib/feed-container.tsx
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@ -1,27 +1,11 @@
import {
ChatItem,
getProcessedHistory,
queryAi,
sendFeedbackAnalytics,
sendQueryAnalytics,
} from '@nx/nx-dev/data-access-ai';
import { sendCustomEvent } from '@nx/nx-dev/feature-analytics'; import { sendCustomEvent } from '@nx/nx-dev/feature-analytics';
import { RefObject, useEffect, useRef, useState } from 'react'; import { RefObject, useEffect, useRef, useState } from 'react';
import { ErrorMessage } from './error-message'; import { ErrorMessage } from './error-message';
import { Feed } from './feed/feed'; import { Feed } from './feed/feed';
import { LoadingState } from './loading-state'; import { LoadingState } from './loading-state';
import { Prompt } from './prompt'; import { Prompt } from './prompt';
import { formatMarkdownSources } from './utils'; import { ChatItem, extractLinksFromSourcesSection } from '@nx/nx-dev/util-ai';
import { Message, useChat } from 'ai/react';
interface LastQueryMetadata {
sources: string[];
textResponse: string;
usage: {
completion_tokens: number;
prompt_tokens: number;
total_tokens: number;
} | null;
}
const assistantWelcome: ChatItem = { const assistantWelcome: ChatItem = {
role: 'assistant', role: 'assistant',
@ -30,13 +14,30 @@ const assistantWelcome: ChatItem = {
}; };
export function FeedContainer(): JSX.Element { export function FeedContainer(): JSX.Element {
const [chatHistory, setChatHistory] = useState<ChatItem[]>([]); const [error, setError] = useState<Error | null>(null);
const [queryError, setQueryError] = useState<any | null>(null); const [startedReply, setStartedReply] = useState(false);
const [isLoading, setIsLoading] = useState(false); const [sources, setSources] = useState<string[]>([]);
const [lastQueryMetadata, setLastQueryMetadata] =
useState<LastQueryMetadata | null>(null);
const feedContainer: RefObject<HTMLDivElement> | undefined = useRef(null); const feedContainer: RefObject<HTMLDivElement> | undefined = useRef(null);
const { messages, input, handleInputChange, handleSubmit, isLoading } =
useChat({
api: '/api/query-ai-handler',
onError: (error) => {
setError(error);
},
onResponse: (_response) => {
setStartedReply(true);
sendCustomEvent('ai_query', 'ai', 'query', undefined, {
query: input,
});
setError(null);
},
onFinish: (response: Message) => {
setStartedReply(false);
setSources(extractLinksFromSourcesSection(response.content));
// Here we have the message id and the timestamp, so we can create a linked list
},
});
useEffect(() => { useEffect(() => {
if (feedContainer.current) { if (feedContainer.current) {
@ -44,78 +45,21 @@ export function FeedContainer(): JSX.Element {
feedContainer.current.getElementsByClassName('feed-item'); feedContainer.current.getElementsByClassName('feed-item');
elements[elements.length - 1].scrollIntoView({ behavior: 'smooth' }); elements[elements.length - 1].scrollIntoView({ behavior: 'smooth' });
} }
}, [chatHistory, isLoading]); }, [messages, isLoading]);
const handleSubmit = async (query: string, currentHistory: ChatItem[]) => {
if (!query) return;
currentHistory.push({ role: 'user', content: query });
setIsLoading(true);
setQueryError(null);
try {
const lastAnswerChatItem =
currentHistory.filter((item) => item.role === 'assistant').pop() ||
null;
// Use previous assistant's answer if it exists
const aiResponse = await queryAi(
query,
lastAnswerChatItem ? lastAnswerChatItem.content : ''
);
// TODO: Save a list of metadata corresponding to each query
// Saving Metadata for usage like feedback and analytics
setLastQueryMetadata({
sources: aiResponse.sources
? aiResponse.sources.map((source) => source.url)
: [],
textResponse: aiResponse.textResponse,
usage: aiResponse.usage || null,
});
let content = aiResponse.textResponse;
if (aiResponse.sourcesMarkdown.length !== 0)
content += formatMarkdownSources(aiResponse.sourcesMarkdown);
// Saving the new chat history used by AI for follow-up prompts
setChatHistory([
...getProcessedHistory(),
{ role: 'assistant', content },
]);
sendCustomEvent('ai_query', 'ai', 'query', undefined, {
query,
...aiResponse.usage,
});
sendQueryAnalytics({
action: 'ai_query',
query,
...aiResponse.usage,
});
} catch (error: any) {
setQueryError(error);
}
setIsLoading(false);
};
const handleFeedback = (statement: 'good' | 'bad', chatItemIndex: number) => { const handleFeedback = (statement: 'good' | 'bad', chatItemIndex: number) => {
const question = chatHistory[chatItemIndex - 1]; // TODO(katerina): Fix this - Read on
const answer = chatHistory[chatItemIndex]; // This is wrong
// We have to make sure to send the query for the actual message that was clicked
// Here we are just sending the last one
const question = messages[chatItemIndex - 1];
const answer = messages[chatItemIndex];
sendCustomEvent('ai_feedback', 'ai', statement, undefined, { sendCustomEvent('ai_feedback', 'ai', statement, undefined, {
query: question ? question.content : 'Could not retrieve the question', query: question ? question.content : 'Could not retrieve the question',
result: answer ? answer.content : 'Could not retrieve the answer', result: answer ? answer.content : 'Could not retrieve the answer',
sources: lastQueryMetadata sources: sources
? JSON.stringify(lastQueryMetadata.sources) ? JSON.stringify(sources)
: 'Could not retrieve last answer sources',
});
sendFeedbackAnalytics({
action: 'evaluation',
result: answer ? answer.content : 'Could not retrieve the answer',
query: question ? question.content : 'Could not retrieve the question',
response: null, // TODO: Use query metadata here
sources: lastQueryMetadata
? JSON.stringify(lastQueryMetadata.sources)
: 'Could not retrieve last answer sources', : 'Could not retrieve last answer sources',
}); });
}; };
@ -141,20 +85,21 @@ export function FeedContainer(): JSX.Element {
className="relative" className="relative"
> >
<Feed <Feed
activity={ activity={!!messages.length ? messages : [assistantWelcome]}
!!chatHistory.length ? chatHistory : [assistantWelcome]
}
handleFeedback={(statement, chatItemIndex) => handleFeedback={(statement, chatItemIndex) =>
handleFeedback(statement, chatItemIndex) handleFeedback(statement, chatItemIndex)
} }
/> />
{isLoading && <LoadingState />} {/* Change this message if it's loading but it's writing as well */}
{queryError && <ErrorMessage error={queryError} />} {isLoading && !startedReply && <LoadingState />}
{error && <ErrorMessage error={error} />}
<div className="sticky bottom-0 left-0 right-0 w-full pt-6 pb-4 bg-gradient-to-t from-white via-white dark:from-slate-900 dark:via-slate-900"> <div className="sticky bottom-0 left-0 right-0 w-full pt-6 pb-4 bg-gradient-to-t from-white via-white dark:from-slate-900 dark:via-slate-900">
<Prompt <Prompt
handleSubmit={(query) => handleSubmit(query, chatHistory)} handleSubmit={handleSubmit}
handleInputChange={handleInputChange}
input={input}
isDisabled={isLoading} isDisabled={isLoading}
/> />
</div> </div>

11
nx-dev/feature-ai/src/lib/feed/feed-answer.tsx
View File

@ -2,12 +2,14 @@ import {
HandThumbDownIcon, HandThumbDownIcon,
HandThumbUpIcon, HandThumbUpIcon,
} from '@heroicons/react/24/outline'; } from '@heroicons/react/24/outline';
import { renderMarkdown } from '@nx/nx-dev/ui-markdoc';
import { cx } from '@nx/nx-dev/ui-primitives'; import { cx } from '@nx/nx-dev/ui-primitives';
import Link from 'next/link';
import { useState } from 'react'; import { useState } from 'react';
import { ChatGptLogo } from './chat-gpt-logo'; import { ChatGptLogo } from './chat-gpt-logo';
import { NrwlLogo } from './nrwl-logo'; import ReactMarkdown from 'react-markdown';
import { renderMarkdown } from '@nx/nx-dev/ui-markdoc';
const callout: string =
'{% callout type="warning" title="Always double-check!" %}The results may not be accurate, so please always double check with our documentation.{% /callout %}\n';
export function FeedAnswer({ export function FeedAnswer({
content, content,
@ -60,7 +62,8 @@ export function FeedAnswer({
</p> </p>
</div> </div>
<div className="mt-2 prose prose-slate dark:prose-invert w-full max-w-none 2xl:max-w-4xl"> <div className="mt-2 prose prose-slate dark:prose-invert w-full max-w-none 2xl:max-w-4xl">
{renderMarkdown(content, { filePath: '' }).node} {!isFirst && renderMarkdown(callout, { filePath: '' }).node}
<ReactMarkdown children={content} />
</div> </div>
{!isFirst && ( {!isFirst && (
<div className="group text-xs flex-1 md:flex md:justify-end gap-4 md:items-center text-slate-400 hover:text-slate-500 transition"> <div className="group text-xs flex-1 md:flex md:justify-end gap-4 md:items-center text-slate-400 hover:text-slate-500 transition">

2
nx-dev/feature-ai/src/lib/feed/feed.tsx
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@ -1,4 +1,4 @@
import { ChatItem } from '@nx/nx-dev/data-access-ai'; import { ChatItem } from '@nx/nx-dev/util-ai';
import { FeedAnswer } from './feed-answer'; import { FeedAnswer } from './feed-answer';
import { FeedQuestion } from './feed-question'; import { FeedQuestion } from './feed-question';

26
nx-dev/feature-ai/src/lib/prompt.tsx
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@ -1,18 +1,27 @@
import { useEffect, useRef, useState } from 'react'; import { ChangeEvent, FormEvent, useEffect, useRef } from 'react';
import { PaperAirplaneIcon } from '@heroicons/react/24/outline'; import { PaperAirplaneIcon } from '@heroicons/react/24/outline';
import { Button } from '@nx/nx-dev/ui-common'; import { Button } from '@nx/nx-dev/ui-common';
import Textarea from 'react-textarea-autosize'; import Textarea from 'react-textarea-autosize';
import { ChatRequestOptions } from 'ai';
export function Prompt({ export function Prompt({
isDisabled, isDisabled,
handleSubmit, handleSubmit,
handleInputChange,
input,
}: { }: {
isDisabled: boolean; isDisabled: boolean;
handleSubmit: (query: string) => void; handleSubmit: (
e: FormEvent<HTMLFormElement>,
chatRequestOptions?: ChatRequestOptions | undefined
) => void;
handleInputChange: (
e: ChangeEvent<HTMLTextAreaElement> | ChangeEvent<HTMLInputElement>
) => void;
input: string;
}) { }) {
const formRef = useRef<HTMLFormElement>(null); const formRef = useRef<HTMLFormElement>(null);
const inputRef = useRef<HTMLTextAreaElement>(null); const inputRef = useRef<HTMLTextAreaElement>(null);
const [inputValue, setInputValue] = useState<string>('');
useEffect(() => { useEffect(() => {
if (inputRef.current) { if (inputRef.current) {
@ -23,13 +32,7 @@ export function Prompt({
return ( return (
<form <form
ref={formRef} ref={formRef}
onSubmit={(event) => { onSubmit={handleSubmit}
event.preventDefault();
if (!inputValue?.trim()) return;
handleSubmit(inputValue);
setInputValue('');
event.currentTarget.reset();
}}
className="relative flex gap-2 max-w-2xl mx-auto py-0 px-2 shadow-lg rounded-md border border-slate-300 bg-white dark:border-slate-900 dark:bg-slate-700" className="relative flex gap-2 max-w-2xl mx-auto py-0 px-2 shadow-lg rounded-md border border-slate-300 bg-white dark:border-slate-900 dark:bg-slate-700"
> >
<div className="overflow-y-auto w-full h-full max-h-[300px]"> <div className="overflow-y-auto w-full h-full max-h-[300px]">
@ -45,7 +48,8 @@ export function Prompt({
} }
}} }}
ref={inputRef} ref={inputRef}
onChange={(event) => setInputValue(event.target.value)} value={input}
onChange={handleInputChange}
id="query-prompt" id="query-prompt"
name="query" name="query"
disabled={isDisabled} disabled={isDisabled}

7
nx-dev/feature-ai/src/lib/utils.ts
View File

@ -1,7 +0,0 @@
export function formatMarkdownSources(sourcesMarkdown: string): string {
return `\n
{% callout type="info" title="Sources" %}
${sourcesMarkdown}
{% /callout %}
\n`;
}

45
nx-dev/nx-dev/pages/api/openai-handler.ts
View File

@ -1,45 +0,0 @@
import { NextRequest } from 'next/server';
const openAiKey = process.env['NX_OPENAI_KEY'];
export const config = {
runtime: 'edge',
};
export default async function handler(request: NextRequest) {
const { action, input } = await request.json();
let apiUrl = 'https://api.openai.com/v1/';
if (action === 'embedding') {
apiUrl += 'embeddings';
} else if (action === 'chatCompletion') {
apiUrl += 'chat/completions';
} else if (action === 'moderation') {
apiUrl += 'moderations';
} else {
return new Response('Invalid action', { status: 400 });
}
try {
const response = await fetch(apiUrl, {
method: 'POST',
headers: {
Authorization: `Bearer ${openAiKey}`,
'Content-Type': 'application/json',
},
body: JSON.stringify(input),
});
const responseData = await response.json();
return new Response(JSON.stringify(responseData), {
status: response.status,
headers: {
'content-type': 'application/json',
},
});
} catch (e) {
console.error('Error processing the request:', e.message);
return new Response(e.message, { status: 500 });
}
}

142
nx-dev/nx-dev/pages/api/query-ai-handler.ts Normal file
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@ -0,0 +1,142 @@
import { NextRequest } from 'next/server';
import {
ChatItem,
CustomError,
DEFAULT_MATCH_COUNT,
DEFAULT_MATCH_THRESHOLD,
MIN_CONTENT_LENGTH,
PROMPT,
PageSection,
appendToStream,
getSupabaseClient,
formatMarkdownSources,
getLastAssistantMessageContent,
getOpenAI,
getUserQuery,
initializeChat,
extractErrorMessage,
// moderateContent,
} from '@nx/nx-dev/util-ai';
import { SupabaseClient } from '@supabase/supabase-js';
import OpenAI from 'openai';
import { OpenAIStream, StreamingTextResponse } from 'ai';
import GPT3Tokenizer from 'gpt3-tokenizer';
import { Stream } from 'openai/streaming';
const supabaseUrl = process.env['NX_NEXT_PUBLIC_SUPABASE_URL'];
const supabaseServiceKey = process.env['NX_SUPABASE_SERVICE_ROLE_KEY_ACTUAL'];
const openAiKey = process.env['NX_OPENAI_KEY'];
const tokenCountLimit =
parseInt(process.env['NX_TOKEN_COUNT_LIMIT'] ?? '2500') > 0
? parseInt(process.env['NX_TOKEN_COUNT_LIMIT'] ?? '2500')
: 2500;
export const config = {
runtime: 'edge',
};
export default async function handler(request: NextRequest) {
try {
const openai = getOpenAI(openAiKey);
const supabaseClient: SupabaseClient<any, 'public', any> =
getSupabaseClient(supabaseUrl, supabaseServiceKey);
const { messages } = (await request.json()) as { messages: ChatItem[] };
const query: string | null = getUserQuery(messages);
const sanitizedQuery = query.trim();
// Moderate the content to comply with OpenAI T&C
// Removing the moderation for now
// to see if it's faster
// await moderateContent(sanitizedQuery, openai);
// We include the previous response,
// to make sure the embeddings (doc sections)
// we get back are relevant.
const embeddingResponse: OpenAI.Embeddings.CreateEmbeddingResponse =
await openai.embeddings.create({
model: 'text-embedding-ada-002',
input: sanitizedQuery + getLastAssistantMessageContent(messages),
});
const {
data: [{ embedding }],
} = embeddingResponse;
// Based on:
// https://github.com/supabase-community/nextjs-openai-doc-search/blob/main/pages/api/vector-search.ts
const { error: matchError, data: pageSections } = await supabaseClient.rpc(
'match_page_sections_2',
{
embedding,
match_threshold: DEFAULT_MATCH_THRESHOLD,
match_count: DEFAULT_MATCH_COUNT,
min_content_length: MIN_CONTENT_LENGTH,
}
);
if (matchError) {
throw new CustomError(
'application_error',
'Failed to match page sections',
matchError
);
}
// Note: this is experimental and quite aggressive. I think it should work
// mainly because we're testing previous response + query.
if (!pageSections || pageSections.length === 0) {
throw new CustomError('user_error', 'No results found.', {
no_results: true,
});
}
const tokenizer = new GPT3Tokenizer({ type: 'gpt3' });
let tokenCount = 0;
let contextText = '';
for (let i = 0; i < (pageSections as PageSection[]).length; i++) {
const pageSection: PageSection = pageSections[i];
const content = pageSection.content;
const encoded = tokenizer.encode(content);
tokenCount += encoded.text.length;
if (tokenCount >= tokenCountLimit) {
break;
}
contextText += `${content.trim()}\n---\n`;
}
const { chatMessages } = initializeChat(
messages,
query,
contextText,
PROMPT
);
const response: Stream<OpenAI.Chat.Completions.ChatCompletionChunk> =
await openai.chat.completions.create({
model: 'gpt-3.5-turbo-16k',
messages: chatMessages,
temperature: 0,
stream: true,
});
const sourcesMarkdown = formatMarkdownSources(pageSections);
const stream = OpenAIStream(response);
const finalStream = await appendToStream(stream, sourcesMarkdown);
return new StreamingTextResponse(finalStream);
} catch (err: unknown) {
console.error('Error: ', err);
const errorResponse = extractErrorMessage(err);
return new Response(JSON.stringify(errorResponse), {
status: 500,
headers: {
'content-type': 'application/json',
},
});
}
}

7
nx-dev/data-access-ai/.eslintrc.json → nx-dev/util-ai/.eslintrc.json
View File

@ -13,6 +13,13 @@
{ {
"files": ["*.js", "*.jsx"], "files": ["*.js", "*.jsx"],
"rules": {} "rules": {}
},
{
"files": ["*.json"],
"parser": "jsonc-eslint-parser",
"rules": {
"@nx/dependency-checks": "error"
}
} }
] ]
} }

11
nx-dev/util-ai/README.md Normal file
View File

@ -0,0 +1,11 @@
# nx-dev-util-ai
This library was generated with [Nx](https://nx.dev).
## Building
Run `nx build nx-dev-util-ai` to build the library.
## Running unit tests
Run `nx test nx-dev-util-ai` to execute the unit tests via [Jest](https://jestjs.io).

4
nx-dev/data-access-ai/jest.config.ts → nx-dev/util-ai/jest.config.ts
View File

@ -1,11 +1,11 @@
/* eslint-disable */ /* eslint-disable */
export default { export default {
displayName: 'nx-dev-data-access-ai', displayName: 'nx-dev-util-ai',
preset: '../../jest.preset.js', preset: '../../jest.preset.js',
testEnvironment: 'node', testEnvironment: 'node',
transform: { transform: {
'^.+\\.[tj]s$': ['ts-jest', { tsconfig: '<rootDir>/tsconfig.spec.json' }], '^.+\\.[tj]s$': ['ts-jest', { tsconfig: '<rootDir>/tsconfig.spec.json' }],
}, },
moduleFileExtensions: ['ts', 'js', 'html'], moduleFileExtensions: ['ts', 'js', 'html'],
coverageDirectory: '../../coverage/nx-dev/data-access-ai', coverageDirectory: '../../coverage/nx-dev/util-ai',
}; };

12
nx-dev/util-ai/package.json Normal file
View File

@ -0,0 +1,12 @@
{
"name": "@nx/nx-dev/util-ai",
"version": "0.0.1",
"dependencies": {
"@supabase/supabase-js": "^2.26.0",
"tslib": "^2.3.0",
"openai": "~4.3.1"
},
"type": "commonjs",
"main": "./src/index.js",
"typings": "./src/index.d.ts"
}

19
nx-dev/data-access-ai/project.json → nx-dev/util-ai/project.json
View File

@ -1,31 +1,34 @@
{ {
"name": "nx-dev-data-access-ai", "name": "nx-dev-util-ai",
"$schema": "../../node_modules/nx/schemas/project-schema.json", "$schema": "../../node_modules/nx/schemas/project-schema.json",
"sourceRoot": "nx-dev/data-access-ai/src", "sourceRoot": "nx-dev/util-ai/src",
"projectType": "library", "projectType": "library",
"targets": { "targets": {
"build": { "build": {
"executor": "@nx/js:tsc", "executor": "@nx/js:tsc",
"outputs": ["{options.outputPath}"], "outputs": ["{options.outputPath}"],
"options": { "options": {
"outputPath": "dist/nx-dev/data-access-ai", "outputPath": "dist/nx-dev/util-ai",
"main": "nx-dev/data-access-ai/src/index.ts", "main": "nx-dev/util-ai/src/index.ts",
"tsConfig": "nx-dev/data-access-ai/tsconfig.lib.json", "tsConfig": "nx-dev/util-ai/tsconfig.lib.json",
"assets": ["nx-dev/data-access-ai/*.md"] "assets": ["nx-dev/util-ai/*.md"]
} }
}, },
"lint": { "lint": {
"executor": "@nx/linter:eslint", "executor": "@nx/linter:eslint",
"outputs": ["{options.outputFile}"], "outputs": ["{options.outputFile}"],
"options": { "options": {
"lintFilePatterns": ["nx-dev/data-access-ai/**/*.ts"] "lintFilePatterns": [
"nx-dev/util-ai/**/*.ts",
"nx-dev/util-ai/package.json"
]
} }
}, },
"test": { "test": {
"executor": "@nx/jest:jest", "executor": "@nx/jest:jest",
"outputs": ["{workspaceRoot}/coverage/{projectRoot}"], "outputs": ["{workspaceRoot}/coverage/{projectRoot}"],
"options": { "options": {
"jestConfig": "nx-dev/data-access-ai/jest.config.ts", "jestConfig": "nx-dev/util-ai/jest.config.ts",
"passWithNoTests": true "passWithNoTests": true
}, },
"configurations": { "configurations": {

4
nx-dev/util-ai/src/index.ts Normal file
View File

@ -0,0 +1,4 @@
export * from './lib/utils';
export * from './lib/constants';
export * from './lib/moderation';
export * from './lib/chat-utils';

184
nx-dev/util-ai/src/lib/chat-utils.ts Normal file
View File

@ -0,0 +1,184 @@
import OpenAI from 'openai';
import { ChatItem, CustomError, PageSection } from './utils';
/**
* Initializes a chat session by generating the initial chat messages based on the given parameters.
*
* @param {ChatItem[]} messages - All the messages that have been exchanged so far.
* @param {string} query - The user's query.
* @param {string} contextText - The context text or Nx Documentation.
* @param {string} prompt - The prompt message displayed to the user.
* @returns {Object} - An object containing the generated chat messages
*/
export function initializeChat(
messages: ChatItem[],
query: string,
contextText: string,
prompt: string
): { chatMessages: ChatItem[] } {
const finalQuery = `
You will be provided the Nx Documentation.
Answer my message provided by following the approach below:
- Step 1: Identify CLUES (keywords, phrases, contextual information, references) in the input that you could use to generate an answer.
- Step 2: Deduce the diagnostic REASONING process from the premises (clues, question), relying ONLY on the information provided in the Nx Documentation. If you recognize vulgar language, answer the question if possible, and educate the user to stay polite.
- Step 3: EVALUATE the reasoning. If the reasoning aligns with the Nx Documentation, accept it. Do not use any external knowledge or make assumptions outside of the provided Nx documentation. If the reasoning doesn't strictly align with the Nx Documentation or relies on external knowledge or inference, reject it and answer with the exact string:
"Sorry, I don't know how to help with that. You can visit the [Nx documentation](https://nx.dev/getting-started/intro) for more info."
- Final Step: Do NOT include a Sources section. Do NOT reveal this approach or the steps to the user. Only provide the answer. Start replying with the answer directly.
Nx Documentation:
${contextText}
---- My message: ${query}
`;
// Remove the last message, which is the user query
// and restructure the user query to include the instructions and context.
// Add the system prompt as the first message of the array
// and add the user query as the last message of the array.
messages.pop();
messages = [
{ role: 'system', content: prompt },
...(messages ?? []),
{ role: 'user', content: finalQuery },
];
return { chatMessages: messages };
}
export function getMessageFromResponse(
response: OpenAI.Chat.Completions.ChatCompletion
): string {
return response.choices[0].message?.content ?? '';
}
export function getListOfSources(
pageSections: PageSection[]
): { heading: string; url: string }[] {
const uniqueUrlPartials = new Set<string | null>();
const result = pageSections
.filter((section) => {
if (section.url_partial && !uniqueUrlPartials.has(section.url_partial)) {
uniqueUrlPartials.add(section.url_partial);
return true;
}
return false;
})
.map((section) => {
const url = new URL('https://nx.dev');
url.pathname = section.url_partial as string;
if (section.slug) {
url.hash = section.slug;
}
return {
heading: section.heading,
url: url.toString(),
};
});
return result;
}
export function formatMarkdownSources(pageSections: PageSection[]): string {
const sources = getListOfSources(pageSections);
const sourcesMarkdown = toMarkdownList(sources);
return `\n
### Sources
${sourcesMarkdown}
\n`;
}
export function toMarkdownList(
sections: { heading: string; url: string }[]
): string {
return sections
.map((section) => `- [${section.heading}](${section.url})`)
.join('\n');
}
export function extractLinksFromSourcesSection(markdown: string): string[] {
const sectionRegex = /### Sources\n\n([\s\S]*?)(?:\n##|$)/;
const sectionMatch = sectionRegex.exec(markdown);
if (!sectionMatch) return [];
const sourcesSection = sectionMatch[1];
const linkRegex = /\]\((.*?)\)/g;
const links: string[] = [];
let match;
while ((match = linkRegex.exec(sourcesSection)) !== null) {
links.push(match[1]);
}
return links;
}
export function removeSourcesSection(markdown: string): string {
const sectionRegex = /### Sources\n\n([\s\S]*?)(?:\n###|$)/;
return markdown.replace(sectionRegex, '').trim();
}
export async function appendToStream(
originalStream: ReadableStream<Uint8Array>,
appendContent: string
): Promise<ReadableStream<Uint8Array>> {
const appendText = new TransformStream({
flush(ctrl) {
ctrl.enqueue(new TextEncoder().encode(appendContent));
ctrl.terminate();
},
});
return originalStream.pipeThrough(appendText);
}
export function getLastAssistantIndex(messages: ChatItem[]): number {
for (let i = messages.length - 1; i >= 0; i--) {
if (messages[i].role === 'assistant') {
return i;
}
}
return -1;
}
export function getLastAssistantMessageContent(messages: ChatItem[]): string {
const indexOfLastAiResponse = getLastAssistantIndex(messages);
if (indexOfLastAiResponse > -1 && messages[indexOfLastAiResponse]) {
return messages[indexOfLastAiResponse].content;
} else {
return '';
}
}
// Not used at the moment, but keep it in case it is needed
export function removeSourcesFromLastAssistantMessage(
messages: ChatItem[]
): ChatItem[] {
const indexOfLastAiResponse = getLastAssistantIndex(messages);
if (indexOfLastAiResponse > -1 && messages[indexOfLastAiResponse]) {
messages[indexOfLastAiResponse].content = removeSourcesSection(
messages[indexOfLastAiResponse].content
);
}
return messages;
}
export function getUserQuery(messages: ChatItem[]): string {
let query: string | null = null;
if (messages?.length > 0) {
const lastMessage = messages[messages.length - 1];
if (lastMessage?.role === 'user') {
query = lastMessage.content;
}
}
if (!query) {
throw new CustomError('user_error', 'Missing query in request data', {
missing_query: true,
});
}
return query;
}

30
nx-dev/util-ai/src/lib/constants.ts Normal file
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@ -0,0 +1,30 @@
export const DEFAULT_MATCH_THRESHOLD = 0.78;
export const DEFAULT_MATCH_COUNT = 15;
export const MIN_CONTENT_LENGTH = 50;
// This limits history to 30 messages back and forth
// It's arbitrary, but also generous
// History length should be based on token count
// This is a temporary solution
export const MAX_HISTORY_LENGTH = 30;
export const PROMPT = `
${`
You are a knowledgeable Nx representative.
Your knowledge is based entirely on the official Nx Documentation.
You can answer queries using ONLY that information.
You cannot answer queries using your own knowledge or experience.
Answer in markdown format. Always give an example, answer as thoroughly as you can, and
always provide a link to relevant documentation
on the https://nx.dev website. All the links you find or post
that look like local or relative links, always prepend with "https://nx.dev".
Your answer should be in the form of a Markdown article
(including related code snippets if available), much like the
existing Nx documentation. Mark the titles and the subsections with the appropriate markdown syntax.
If you are unsure and cannot find an answer in the Nx Documentation, say
"Sorry, I don't know how to help with that. You can visit the [Nx documentation](https://nx.dev/getting-started/intro) for more info."
Remember, answer the question using ONLY the information provided in the Nx Documentation.
`
.replace(/\s+/g, ' ')
.trim()}
`;

21
nx-dev/util-ai/src/lib/moderation.ts Normal file
View File

@ -0,0 +1,21 @@
import OpenAI from 'openai';
import { CustomError } from './utils';
export async function moderateContent(sanitizedQuery: string, openai: OpenAI) {
try {
const moderationResponse = await openai.moderations.create({
input: sanitizedQuery,
});
const [results] = moderationResponse.results;
if (results.flagged) {
throw new CustomError('user_error', 'Flagged content', {
flagged: true,
categories: results.categories,
});
}
} catch (e) {
console.error('Error when moderating content: ', e);
}
}

96
nx-dev/util-ai/src/lib/utils.ts Normal file
View File

@ -0,0 +1,96 @@
import OpenAI from 'openai';
import { SupabaseClient, createClient } from '@supabase/supabase-js';
let openai: OpenAI;
let supabaseClient: SupabaseClient<any, 'public', any>;
export function getOpenAI(openAiKey?: string): OpenAI {
if (openai) return openai;
if (!openAiKey) {
throw new CustomError(
'application_error',
'Missing environment variable NX_OPENAI_KEY',
{
missing_key: true,
}
);
}
openai = new OpenAI({ apiKey: openAiKey });
return openai;
}
export function getSupabaseClient(
supabaseUrl?: string,
supabaseServiceKey?: string
): SupabaseClient<any, 'public', any> {
if (supabaseClient) return supabaseClient;
if (!supabaseUrl) {
throw new CustomError(
'application_error',
'Missing environment variable NX_NEXT_PUBLIC_SUPABASE_URL',
{ missing_key: true }
);
}
if (!supabaseServiceKey) {
throw new CustomError(
'application_error',
'Missing environment variable NX_SUPABASE_SERVICE_ROLE_KEY',
{ missing_key: true }
);
}
supabaseClient = createClient(
supabaseUrl as string,
supabaseServiceKey as string
);
return supabaseClient;
}
export class CustomError extends Error {
public type: string;
public data: Record<string, any>;
constructor(
type: string = 'application_error',
message: string,
data: Record<string, any> = {}
) {
super(message);
this.type = type;
this.data = data;
}
}
export interface PageSection {
id: number;
page_id: number;
content: string;
heading: string;
similarity: number;
slug: string;
url_partial: string | null;
}
export interface ChatItem {
role: 'system' | 'user' | 'assistant' | 'function';
content: string;
}
export interface ErrorResponse {
message: string;
data?: any;
}
export function extractErrorMessage(err: unknown): ErrorResponse {
if (err instanceof CustomError) {
return { message: err.message, data: err.data };
}
if (typeof err === 'object' && err !== null) {
const errorObj = err as { [key: string]: any };
const message =
errorObj['message'] || errorObj['error']?.message || 'Unknown error';
return { message, data: errorObj['data'] || null };
}
return { message: 'Unknown error' };
}

4
nx-dev/data-access-ai/tsconfig.json → nx-dev/util-ai/tsconfig.json
View File

@ -7,9 +7,7 @@
"noImplicitOverride": true, "noImplicitOverride": true,
"noPropertyAccessFromIndexSignature": true, "noPropertyAccessFromIndexSignature": true,
"noImplicitReturns": true, "noImplicitReturns": true,
"noFallthroughCasesInSwitch": true, "noFallthroughCasesInSwitch": true
"target": "es2021",
"lib": ["es2021", "DOM"]
}, },
"files": [], "files": [],
"include": [], "include": [],

1
nx-dev/data-access-ai/tsconfig.lib.json → nx-dev/util-ai/tsconfig.lib.json
View File

@ -3,6 +3,7 @@
"compilerOptions": { "compilerOptions": {
"outDir": "../../dist/out-tsc", "outDir": "../../dist/out-tsc",
"declaration": true, "declaration": true,
"lib": ["dom", "es2019"],
"types": ["node"] "types": ["node"]
}, },
"include": ["src/**/*.ts"], "include": ["src/**/*.ts"],

0
nx-dev/data-access-ai/tsconfig.spec.json → nx-dev/util-ai/tsconfig.spec.json
View File

10
package.json
View File

@ -65,8 +65,10 @@
"@ngrx/router-store": "~16.0.0", "@ngrx/router-store": "~16.0.0",
"@ngrx/store": "~16.0.0", "@ngrx/store": "~16.0.0",
"@nguniversal/builders": "~16.2.0", "@nguniversal/builders": "~16.2.0",
"@nx/angular": "16.8.0-beta.3",
"@nx/cypress": "16.8.0-beta.3", "@nx/cypress": "16.8.0-beta.3",
"@nx/devkit": "16.8.0-beta.3", "@nx/devkit": "16.8.0-beta.3",
"@nx/esbuild": "16.8.0-beta.3",
"@nx/eslint-plugin": "16.8.0-beta.3", "@nx/eslint-plugin": "16.8.0-beta.3",
"@nx/jest": "16.8.0-beta.3", "@nx/jest": "16.8.0-beta.3",
"@nx/js": "16.8.0-beta.3", "@nx/js": "16.8.0-beta.3",
@ -77,8 +79,6 @@
"@nx/storybook": "16.8.0-beta.3", "@nx/storybook": "16.8.0-beta.3",
"@nx/web": "16.8.0-beta.3", "@nx/web": "16.8.0-beta.3",
"@nx/webpack": "16.8.0-beta.3", "@nx/webpack": "16.8.0-beta.3",
"@nx/esbuild": "16.8.0-beta.3",
"@nx/angular": "16.8.0-beta.3",
"@parcel/watcher": "2.0.4", "@parcel/watcher": "2.0.4",
"@phenomnomnominal/tsquery": "~5.0.1", "@phenomnomnominal/tsquery": "~5.0.1",
"@playwright/test": "^1.36.1", "@playwright/test": "^1.36.1",
@ -134,7 +134,7 @@
"@xstate/immer": "0.3.1", "@xstate/immer": "0.3.1",
"@xstate/inspect": "0.7.0", "@xstate/inspect": "0.7.0",
"@xstate/react": "3.0.1", "@xstate/react": "3.0.1",
"ai": "^2.1.15", "ai": "^2.2.10",
"ajv": "^8.11.0", "ajv": "^8.11.0",
"autoprefixer": "10.4.13", "autoprefixer": "10.4.13",
"babel-jest": "29.4.3", "babel-jest": "29.4.3",
@ -230,7 +230,7 @@
"nx-cloud": "16.4.0-beta.6", "nx-cloud": "16.4.0-beta.6",
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"parse5": "4.0.0", "parse5": "4.0.0",
@ -242,6 +242,7 @@
"prettier-plugin-tailwindcss": "^0.1.5", "prettier-plugin-tailwindcss": "^0.1.5",
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@ -374,4 +375,3 @@
} }
} }
} }

403
pnpm-lock.yaml generated
View File

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ajv: ajv:
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@ -766,8 +766,8 @@ devDependencies:
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version: 8.4.0 version: 8.4.0
openai: openai:
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ora: ora:
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@ -801,6 +801,9 @@ devDependencies:
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react-markdown:
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react-redux: react-redux:
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version: 8.0.5(@types/react-dom@18.2.6)(@types/react@18.2.14)(react-dom@18.2.0)(react@18.2.0)(redux@4.2.0) version: 8.0.5(@types/react-dom@18.2.6)(@types/react@18.2.14)(react-dom@18.2.0)(react@18.2.0)(redux@4.2.0)
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engines: {node: '>=14.6'} engines: {node: '>=14.6'}
peerDependencies: peerDependencies:
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svelte: ^4.0.0 solid-js: ^1.7.7
svelte: ^3.0.0 || ^4.0.0
vue: ^3.3.4 vue: ^3.3.4
peerDependenciesMeta: peerDependenciesMeta:
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solid-js:
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svelte: svelte:
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@ -11304,12 +11309,19 @@ packages:
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svelte: 3.59.2 solid-swr-store: 0.10.7(solid-js@1.7.11)(swr-store@0.10.6)
swr: 2.1.5(react@18.2.0) sswr: 2.0.0(svelte@4.2.0)
swrv: 1.0.3(vue@3.3.4) svelte: 4.2.0
swr: 2.2.0(react@18.2.0)
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swrv: 1.0.4(vue@3.3.4)
vue: 3.3.4 vue: 3.3.4
transitivePeerDependencies:
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@ -11784,14 +11802,6 @@ packages:
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@ -12142,9 +12158,17 @@ packages:
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@ -14510,6 +14556,13 @@ packages:
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engines: {node: '>= 0.4'} engines: {node: '>= 0.4'}
/svelte@3.59.2: /svelte@4.2.0:
resolution: {integrity: sha512-vzSyuGr3eEoAtT/A6bmajosJZIUWySzY2CzB3w2pgPvnkUjGqlDnsNnA0PMO+mMAhuyMul6C2uuZzY6ELSkzyA==} resolution: {integrity: sha512-kVsdPjDbLrv74SmLSUzAsBGquMs4MPgWGkGLpH+PjOYnFOziAvENVzgJmyOCV2gntxE32aNm8/sqNKD6LbIpeQ==}
engines: {node: '>= 8'} engines: {node: '>=16'}
dependencies:
'@ampproject/remapping': 2.2.1
'@jridgewell/sourcemap-codec': 1.4.15
'@jridgewell/trace-mapping': 0.3.18
acorn: 8.10.0
aria-query: 5.3.0
axobject-query: 3.2.1
code-red: 1.0.4
css-tree: 2.3.1
estree-walker: 3.0.3
is-reference: 3.0.1
locate-character: 3.0.0
magic-string: 0.30.2
periscopic: 3.1.0
dev: true dev: true
/svg-parser@2.0.4: /svg-parser@2.0.4:
@ -25858,8 +26125,15 @@ packages:
webpack: 5.88.0(@swc/core@1.3.51)(esbuild@0.19.2) webpack: 5.88.0(@swc/core@1.3.51)(esbuild@0.19.2)
dev: true dev: true
/swr@2.1.5(react@18.2.0): /swr-store@0.10.6:
resolution: {integrity: sha512-/OhfZMcEpuz77KavXST5q6XE9nrOBOVcBLWjMT+oAE/kQHyE3PASrevXCtQDZ8aamntOfFkbVJp7Il9tNBQWrw==} resolution: {integrity: sha512-xPjB1hARSiRaNNlUQvWSVrG5SirCjk2TmaUyzzvk69SZQan9hCJqw/5rG9iL7xElHU784GxRPISClq4488/XVw==}
engines: {node: '>=10'}
dependencies:
dequal: 2.0.3
dev: true
/swr@2.2.0(react@18.2.0):
resolution: {integrity: sha512-AjqHOv2lAhkuUdIiBu9xbuettzAzWXmCEcLONNKJRba87WAefz8Ca9d6ds/SzrPc235n1IxWYdhJ2zF3MNUaoQ==}
peerDependencies: peerDependencies:
react: ^16.11.0 || ^17.0.0 || ^18.0.0 react: ^16.11.0 || ^17.0.0 || ^18.0.0
dependencies: dependencies:
@ -25867,12 +26141,12 @@ packages:
use-sync-external-store: 1.2.0(react@18.2.0) use-sync-external-store: 1.2.0(react@18.2.0)
dev: true dev: true
/swrev@3.0.0: /swrev@4.0.0:
resolution: {integrity: sha512-QJuZiptdOmbDY45pECBRVEgnoBlOKjeT2MWVz04wKHpWX15hM3P7EjcIbHDg5yLoPCMQ7to3349MEE+l9QF5HA==} resolution: {integrity: sha512-LqVcOHSB4cPGgitD1riJ1Hh4vdmITOp+BkmfmXRh4hSF/t7EnS4iD+SOTmq7w5pPm/SiPeto4ADbKS6dHUDWFA==}
dev: true dev: true
/swrv@1.0.3(vue@3.3.4): /swrv@1.0.4(vue@3.3.4):
resolution: {integrity: sha512-sl+eLEE+aPPjhP1E8gQ75q3RPRyw5Gd/kROnrTFo3+LkCeLskv7F+uAl5W97wgJkzitobL6FLsRPVm0DgIgN8A==} resolution: {integrity: sha512-zjEkcP8Ywmj+xOJW3lIT65ciY/4AL4e/Or7Gj0MzU3zBJNMdJiT8geVZhINavnlHRMMCcJLHhraLTAiDOTmQ9g==}
peerDependencies: peerDependencies:
vue: '>=3.2.26 < 4' vue: '>=3.2.26 < 4'
dependencies: dependencies:
@ -26399,6 +26673,10 @@ packages:
engines: {node: ^14.17.0 || ^16.13.0 || >=18.0.0} engines: {node: ^14.17.0 || ^16.13.0 || >=18.0.0}
dev: true dev: true
/trim-lines@3.0.1:
resolution: {integrity: sha512-kRj8B+YHZCc9kQYdWfJB2/oUl9rA99qbowYYBtr4ui4mZyAQ2JpvVBd/6U2YloATfqBhBTSMhTpgBHtU0Mf3Rg==}
dev: true
/trim-newlines@3.0.1: /trim-newlines@3.0.1:
resolution: {integrity: sha512-c1PTsA3tYrIsLGkJkzHF+w9F2EyxfXGo4UyJc4pFL++FMjnq0HJS69T3M7d//gKrFKwy429bouPescbjecU+Zw==} resolution: {integrity: sha512-c1PTsA3tYrIsLGkJkzHF+w9F2EyxfXGo4UyJc4pFL++FMjnq0HJS69T3M7d//gKrFKwy429bouPescbjecU+Zw==}
engines: {node: '>=8'} engines: {node: '>=8'}
@ -26411,6 +26689,10 @@ packages:
escape-string-regexp: 5.0.0 escape-string-regexp: 5.0.0
dev: true dev: true
/trough@2.1.0:
resolution: {integrity: sha512-AqTiAOLcj85xS7vQ8QkAV41hPDIJ71XJB4RCUrzo/1GM2CQwhkJGaf9Hgr7BOugMRpgGUrqRg/DrBDl4H40+8g==}
dev: true
/ts-dedent@2.2.0: /ts-dedent@2.2.0:
resolution: {integrity: sha512-q5W7tVM71e2xjHZTlgfTDoPF/SmqKG5hddq9SzR49CH2hayqRKJtQ4mtRlSxKaJlR/+9rEM+mnBHf7I2/BQcpQ==} resolution: {integrity: sha512-q5W7tVM71e2xjHZTlgfTDoPF/SmqKG5hddq9SzR49CH2hayqRKJtQ4mtRlSxKaJlR/+9rEM+mnBHf7I2/BQcpQ==}
engines: {node: '>=6.10'} engines: {node: '>=6.10'}
@ -26845,6 +27127,18 @@ packages:
engines: {node: '>=4'} engines: {node: '>=4'}
dev: true dev: true
/unified@10.1.2:
resolution: {integrity: sha512-pUSWAi/RAnVy1Pif2kAoeWNBa3JVrx0MId2LASj8G+7AiHWoKZNTomq6LG326T68U7/e263X6fTdcXIy7XnF7Q==}
dependencies:
'@types/unist': 2.0.6
bail: 2.0.2
extend: 3.0.2
is-buffer: 2.0.5
is-plain-obj: 4.1.0
trough: 2.1.0
vfile: 5.3.7
dev: true
/union@0.5.0: /union@0.5.0:
resolution: {integrity: sha512-N6uOhuW6zO95P3Mel2I2zMsbsanvvtgn6jVqJv4vbVcz/JN0OkL9suomjQGmWtxJQXOCqUJvquc1sMeNz/IwlA==} resolution: {integrity: sha512-N6uOhuW6zO95P3Mel2I2zMsbsanvvtgn6jVqJv4vbVcz/JN0OkL9suomjQGmWtxJQXOCqUJvquc1sMeNz/IwlA==}
engines: {node: '>= 0.8.0'} engines: {node: '>= 0.8.0'}
@ -26893,6 +27187,10 @@ packages:
'@types/unist': 3.0.0 '@types/unist': 3.0.0
dev: true dev: true
/unist-util-generated@2.0.1:
resolution: {integrity: sha512-qF72kLmPxAw0oN2fwpWIqbXAVyEqUzDHMsbtPvOudIlUzXYFIeQIuxXQCRCFh22B7cixvU0MG7m3MW8FTq/S+A==}
dev: true
/unist-util-is@4.1.0: /unist-util-is@4.1.0:
resolution: {integrity: sha512-ZOQSsnce92GrxSqlnEEseX0gi7GH9zTJZ0p9dtu87WRb/37mMPO2Ilx1s/t9vBHrFhbgweUwb+t7cIn5dxPhZg==} resolution: {integrity: sha512-ZOQSsnce92GrxSqlnEEseX0gi7GH9zTJZ0p9dtu87WRb/37mMPO2Ilx1s/t9vBHrFhbgweUwb+t7cIn5dxPhZg==}
dev: true dev: true
@ -26903,6 +27201,12 @@ packages:
'@types/unist': 2.0.6 '@types/unist': 2.0.6
dev: true dev: true
/unist-util-position@4.0.4:
resolution: {integrity: sha512-kUBE91efOWfIVBo8xzh/uZQ7p9ffYRtUbMRZBNFYwf0RK8koUMx6dGUfwylLOKmaT2cs4wSW96QoYUSXAyEtpg==}
dependencies:
'@types/unist': 2.0.6
dev: true
/unist-util-stringify-position@3.0.3: /unist-util-stringify-position@3.0.3:
resolution: {integrity: sha512-k5GzIBZ/QatR8N5X2y+drfpWG8IDBzdnVj6OInRNWm1oXrzydiaAT2OQiA8DPRRZyAKb9b6I2a6PxYklZD0gKg==} resolution: {integrity: sha512-k5GzIBZ/QatR8N5X2y+drfpWG8IDBzdnVj6OInRNWm1oXrzydiaAT2OQiA8DPRRZyAKb9b6I2a6PxYklZD0gKg==}
dependencies: dependencies:
@ -27379,6 +27683,22 @@ packages:
extsprintf: 1.4.1 extsprintf: 1.4.1
dev: true dev: true
/vfile-message@3.1.4:
resolution: {integrity: sha512-fa0Z6P8HUrQN4BZaX05SIVXic+7kE3b05PWAtPuYP9QLHsLKYR7/AlLW3NtOrpXRLeawpDLMsVkmk5DG0NXgWw==}
dependencies:
'@types/unist': 2.0.6
unist-util-stringify-position: 3.0.3
dev: true
/vfile@5.3.7:
resolution: {integrity: sha512-r7qlzkgErKjobAmyNIkkSpizsFPYiUPuJb5pNW1RB4JcYVZhs4lIbVqk8XPk033CV/1z8ss5pkax8SuhGpcG8g==}
dependencies:
'@types/unist': 2.0.6
is-buffer: 2.0.5
unist-util-stringify-position: 3.0.3
vfile-message: 3.1.4
dev: true
/vite-node@0.32.0(@types/node@18.16.9)(less@4.1.3)(sass@1.55.0)(stylus@0.59.0): /vite-node@0.32.0(@types/node@18.16.9)(less@4.1.3)(sass@1.55.0)(stylus@0.59.0):
resolution: {integrity: sha512-220P/y8YacYAU+daOAqiGEFXx2A8AwjadDzQqos6wSukjvvTWNqleJSwoUn0ckyNdjHIKoxn93Nh1vWBqEKr3Q==} resolution: {integrity: sha512-220P/y8YacYAU+daOAqiGEFXx2A8AwjadDzQqos6wSukjvvTWNqleJSwoUn0ckyNdjHIKoxn93Nh1vWBqEKr3Q==}
engines: {node: '>=v14.18.0'} engines: {node: '>=v14.18.0'}
@ -27658,6 +27978,11 @@ packages:
setimmediate-napi: 1.0.6 setimmediate-napi: 1.0.6
dev: false dev: false
/web-streams-polyfill@4.0.0-beta.3:
resolution: {integrity: sha512-QW95TCTaHmsYfHDybGMwO5IJIM93I/6vTRk+daHTWFPhwh+C8Cg7j7XyKrwrj8Ib6vYXe0ocYNrmzY4xAAN6ug==}
engines: {node: '>= 14'}
dev: true
/webidl-conversions@3.0.1: /webidl-conversions@3.0.1:
resolution: {integrity: sha512-2JAn3z8AR6rjK8Sm8orRC0h/bcl/DqL7tRPdGZ4I1CjdF+EaMLmYxBHyXuKL849eucPFhvBoxMsflfOb8kxaeQ==} resolution: {integrity: sha512-2JAn3z8AR6rjK8Sm8orRC0h/bcl/DqL7tRPdGZ4I1CjdF+EaMLmYxBHyXuKL849eucPFhvBoxMsflfOb8kxaeQ==}
dev: true dev: true

17
tools/documentation/create-embeddings/src/main.mts
View File

@ -6,8 +6,7 @@ import { config as loadDotEnvFile } from 'dotenv';
import { expand } from 'dotenv-expand'; import { expand } from 'dotenv-expand';
import { readFile } from 'fs/promises'; import { readFile } from 'fs/promises';
import 'openai'; import 'openai';
import { Configuration, OpenAIApi } from 'openai'; import OpenAI from 'openai';
import { inspect } from 'util';
import yargs from 'yargs'; import yargs from 'yargs';
import { createHash } from 'crypto'; import { createHash } from 'crypto';
import GithubSlugger from 'github-slugger'; import GithubSlugger from 'github-slugger';
@ -298,21 +297,15 @@ async function generateEmbeddings() {
const input = content.replace(/\n/g, ' '); const input = content.replace(/\n/g, ' ');
try { try {
const configuration = new Configuration({ const openai = new OpenAI({
apiKey: process.env.NX_OPENAI_KEY, apiKey: process.env.NX_OPENAI_KEY,
}); });
const openai = new OpenAIApi(configuration); const embeddingResponse = await openai.embeddings.create({
const embeddingResponse = await openai.createEmbedding({
model: 'text-embedding-ada-002', model: 'text-embedding-ada-002',
input, input,
}); });
if (embeddingResponse.status !== 200) { const [responseData] = embeddingResponse.data;
throw new Error(inspect(embeddingResponse.data, false, 2));
}
const [responseData] = embeddingResponse.data.data;
const { error: insertPageSectionError, data: pageSection } = const { error: insertPageSectionError, data: pageSection } =
await supabaseClient await supabaseClient
@ -323,7 +316,7 @@ async function generateEmbeddings() {
heading, heading,
content, content,
url_partial, url_partial,
token_count: embeddingResponse.data.usage.total_tokens, token_count: embeddingResponse.usage.total_tokens,
embedding: responseData.embedding, embedding: responseData.embedding,
}) })
.select() .select()

2
tsconfig.base.json
View File

@ -47,7 +47,6 @@
"@nx/next/*": ["packages/next/*"], "@nx/next/*": ["packages/next/*"],
"@nx/node": ["packages/node"], "@nx/node": ["packages/node"],
"@nx/node/*": ["packages/node/*"], "@nx/node/*": ["packages/node/*"],
"@nx/nx-dev/data-access-ai": ["nx-dev/data-access-ai/src/index.ts"],
"@nx/nx-dev/data-access-documents": [ "@nx/nx-dev/data-access-documents": [
"nx-dev/data-access-documents/src/index.ts" "nx-dev/data-access-documents/src/index.ts"
], ],
@ -87,6 +86,7 @@
"@nx/nx-dev/ui-references": ["nx-dev/ui-references/src/index.ts"], "@nx/nx-dev/ui-references": ["nx-dev/ui-references/src/index.ts"],
"@nx/nx-dev/ui-sponsor-card": ["nx-dev/ui-sponsor-card/src/index.ts"], "@nx/nx-dev/ui-sponsor-card": ["nx-dev/ui-sponsor-card/src/index.ts"],
"@nx/nx-dev/ui-theme": ["nx-dev/ui-theme/src/index.ts"], "@nx/nx-dev/ui-theme": ["nx-dev/ui-theme/src/index.ts"],
"@nx/nx-dev/util-ai": ["nx-dev/util-ai/src/index.ts"],
"@nx/playwright": ["packages/playwright/index.ts"], "@nx/playwright": ["packages/playwright/index.ts"],
"@nx/plugin": ["packages/plugin"], "@nx/plugin": ["packages/plugin"],
"@nx/plugin/*": ["packages/plugin/*"], "@nx/plugin/*": ["packages/plugin/*"],