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llama : move end-user examples to tools directory (#13249)

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* llama : move end-user examples to tools directory

---------

Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
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//@ts-check
// Helpers to work with different data types
// by Humans for All
//
/**
* Given the limited context size of local LLMs and , many a times when context gets filled
* between the prompt and the response, it can lead to repeating text garbage generation.
* And many a times setting penalty wrt repeatation leads to over-intelligent garbage
* repeatation with slight variations. These garbage inturn can lead to overloading of the
* available model context, leading to less valuable response for subsequent prompts/queries,
* if chat history is sent to ai model.
*
* So two simple minded garbage trimming logics are experimented below.
* * one based on progressively-larger-substring-based-repeat-matching-with-partial-skip and
* * another based on char-histogram-driven garbage trimming.
* * in future characteristic of histogram over varying lengths could be used to allow for
* a more aggressive and adaptive trimming logic.
*/
/**
* Simple minded logic to help remove repeating garbage at end of the string.
* The repeatation needs to be perfectly matching.
*
* The logic progressively goes on probing for longer and longer substring based
* repeatation, till there is no longer repeatation. Inturn picks the one with
* the longest chain.
*
* @param {string} sIn
* @param {number} maxSubL
* @param {number} maxMatchLenThreshold
*/
export function trim_repeat_garbage_at_end(sIn, maxSubL=10, maxMatchLenThreshold=40) {
let rCnt = [0];
let maxMatchLen = maxSubL;
let iMML = -1;
for(let subL=1; subL < maxSubL; subL++) {
rCnt.push(0);
let i;
let refS = sIn.substring(sIn.length-subL, sIn.length);
for(i=sIn.length; i > 0; i -= subL) {
let curS = sIn.substring(i-subL, i);
if (refS != curS) {
let curMatchLen = rCnt[subL]*subL;
if (maxMatchLen < curMatchLen) {
maxMatchLen = curMatchLen;
iMML = subL;
}
break;
}
rCnt[subL] += 1;
}
}
console.debug("DBUG:DU:TrimRepeatGarbage:", rCnt);
if ((iMML == -1) || (maxMatchLen < maxMatchLenThreshold)) {
return {trimmed: false, data: sIn};
}
console.debug("DBUG:TrimRepeatGarbage:TrimmedCharLen:", maxMatchLen);
let iEnd = sIn.length - maxMatchLen;
return { trimmed: true, data: sIn.substring(0, iEnd) };
}
/**
* Simple minded logic to help remove repeating garbage at end of the string, till it cant.
* If its not able to trim, then it will try to skip a char at end and then trim, a few times.
* This ensures that even if there are multiple runs of garbage with different patterns, the
* logic still tries to munch through them.
*
* @param {string} sIn
* @param {number} maxSubL
* @param {number | undefined} [maxMatchLenThreshold]
*/
export function trim_repeat_garbage_at_end_loop(sIn, maxSubL, maxMatchLenThreshold, skipMax=16) {
let sCur = sIn;
let sSaved = "";
let iTry = 0;
while(true) {
let got = trim_repeat_garbage_at_end(sCur, maxSubL, maxMatchLenThreshold);
if (got.trimmed != true) {
if (iTry == 0) {
sSaved = got.data;
}
iTry += 1;
if (iTry >= skipMax) {
return sSaved;
}
got.data = got.data.substring(0,got.data.length-1);
} else {
iTry = 0;
}
sCur = got.data;
}
}
/**
* A simple minded try trim garbage at end using histogram driven characteristics.
* There can be variation in the repeatations, as long as no new char props up.
*
* This tracks the chars and their frequency in a specified length of substring at the end
* and inturn checks if moving further into the generated text from the end remains within
* the same char subset or goes beyond it and based on that either trims the string at the
* end or not. This allows to filter garbage at the end, including even if there are certain
* kind of small variations in the repeated text wrt position of seen chars.
*
* Allow the garbage to contain upto maxUniq chars, but at the same time ensure that
* a given type of char ie numerals or alphabets or other types dont cross the specified
* maxType limit. This allows intermixed text garbage to be identified and trimmed.
*
* ALERT: This is not perfect and only provides a rough garbage identification logic.
* Also it currently only differentiates between character classes wrt english.
*
* @param {string} sIn
* @param {number} maxType
* @param {number} maxUniq
* @param {number} maxMatchLenThreshold
*/
export function trim_hist_garbage_at_end(sIn, maxType, maxUniq, maxMatchLenThreshold) {
if (sIn.length < maxMatchLenThreshold) {
return { trimmed: false, data: sIn };
}
let iAlp = 0;
let iNum = 0;
let iOth = 0;
// Learn
let hist = {};
let iUniq = 0;
for(let i=0; i<maxMatchLenThreshold; i++) {
let c = sIn[sIn.length-1-i];
if (c in hist) {
hist[c] += 1;
} else {
if(c.match(/[0-9]/) != null) {
iNum += 1;
} else if(c.match(/[A-Za-z]/) != null) {
iAlp += 1;
} else {
iOth += 1;
}
iUniq += 1;
if (iUniq >= maxUniq) {
break;
}
hist[c] = 1;
}
}
console.debug("DBUG:TrimHistGarbage:", hist);
if ((iAlp > maxType) || (iNum > maxType) || (iOth > maxType)) {
return { trimmed: false, data: sIn };
}
// Catch and Trim
for(let i=0; i < sIn.length; i++) {
let c = sIn[sIn.length-1-i];
if (!(c in hist)) {
if (i < maxMatchLenThreshold) {
return { trimmed: false, data: sIn };
}
console.debug("DBUG:TrimHistGarbage:TrimmedCharLen:", i);
return { trimmed: true, data: sIn.substring(0, sIn.length-i+1) };
}
}
console.debug("DBUG:TrimHistGarbage:Trimmed fully");
return { trimmed: true, data: "" };
}
/**
* Keep trimming repeatedly using hist_garbage logic, till you no longer can.
* This ensures that even if there are multiple runs of garbage with different patterns,
* the logic still tries to munch through them.
*
* @param {any} sIn
* @param {number} maxType
* @param {number} maxUniq
* @param {number} maxMatchLenThreshold
*/
export function trim_hist_garbage_at_end_loop(sIn, maxType, maxUniq, maxMatchLenThreshold) {
let sCur = sIn;
while (true) {
let got = trim_hist_garbage_at_end(sCur, maxType, maxUniq, maxMatchLenThreshold);
if (!got.trimmed) {
return got.data;
}
sCur = got.data;
}
}
/**
* Try trim garbage at the end by using both the hist-driven-garbage-trimming as well as
* skip-a-bit-if-reqd-then-repeat-pattern-based-garbage-trimming, with blind retrying.
* @param {string} sIn
*/
export function trim_garbage_at_end(sIn) {
let sCur = sIn;
for(let i=0; i<2; i++) {
sCur = trim_hist_garbage_at_end_loop(sCur, 8, 24, 72);
sCur = trim_repeat_garbage_at_end_loop(sCur, 32, 72, 12);
}
return sCur;
}
/**
* NewLines array helper.
* Allow for maintaining a list of lines.
* Allow for a line to be builtup/appended part by part.
*/
export class NewLines {
constructor() {
/** @type {string[]} */
this.lines = [];
}
/**
* Extracts lines from the passed string and inturn either
* append to a previous partial line or add a new line.
* @param {string} sLines
*/
add_append(sLines) {
let aLines = sLines.split("\n");
let lCnt = 0;
for(let line of aLines) {
lCnt += 1;
// Add back newline removed if any during split
if (lCnt < aLines.length) {
line += "\n";
} else {
if (sLines.endsWith("\n")) {
line += "\n";
}
}
// Append if required
if (lCnt == 1) {
let lastLine = this.lines[this.lines.length-1];
if (lastLine != undefined) {
if (!lastLine.endsWith("\n")) {
this.lines[this.lines.length-1] += line;
continue;
}
}
}
// Add new line
this.lines.push(line);
}
}
/**
* Shift the oldest/earliest/0th line in the array. [Old-New|Earliest-Latest]
* Optionally control whether only full lines (ie those with newline at end) will be returned
* or will a partial line without a newline at end (can only be the last line) be returned.
* @param {boolean} bFullWithNewLineOnly
*/
shift(bFullWithNewLineOnly=true) {
let line = this.lines[0];
if (line == undefined) {
return undefined;
}
if ((line[line.length-1] != "\n") && bFullWithNewLineOnly){
return undefined;
}
return this.lines.shift();
}
}

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<!DOCTYPE html>
<html lang="en">
<head>
<title>SimpleChat LlamaCppEtal </title>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<meta name="message" content="Save Nature Save Earth" />
<meta name="description" content="SimpleChat: trigger LLM web service endpoints /chat/completions and /completions, single/multi chat sessions" />
<meta name="author" content="by Humans for All" />
<meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate" />
<script type="importmap">
{
"imports": {
"datautils": "./datautils.mjs",
"ui": "./ui.mjs"
}
}
</script>
<script src="simplechat.js" type="module" defer></script>
<link rel="stylesheet" href="simplechat.css" />
</head>
<body>
<div class="samecolumn" id="fullbody">
<div class="sameline" id="heading">
<p class="heading flex-grow" > <b> SimpleChat </b> </p>
<button id="settings">Settings</button>
</div>
<div id="sessions-div" class="sameline"></div>
<hr>
<div class="sameline">
<label for="system-in">System</label>
<textarea name="system" id="system-in" rows="2" placeholder="e.g. you are a helpful ai assistant, who provides concise answers" class="flex-grow"></textarea>
</div>
<hr>
<div id="chat-div">
<p> You need to have javascript enabled.</p>
</div>
<hr>
<div class="sameline">
<textarea id="user-in" class="flex-grow" rows="2" placeholder="enter your query to the ai model here" ></textarea>
<button id="user-btn">submit</button>
</div>
</div>
</body>
</html>

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# SimpleChat
by Humans for All.
## quickstart
To run from the build dir
bin/llama-server -m path/model.gguf --path ../tools/server/public_simplechat
Continue reading for the details.
## overview
This simple web frontend, allows triggering/testing the server's /completions or /chat/completions endpoints
in a simple way with minimal code from a common code base. Inturn additionally it tries to allow single or
multiple independent back and forth chatting to an extent, with the ai llm model at a basic level, with their
own system prompts.
This allows seeing the generated text / ai-model response in oneshot at the end, after it is fully generated,
or potentially as it is being generated, in a streamed manner from the server/ai-model.
![Chat and Settings screens](./simplechat_screens.webp "Chat and Settings screens")
Auto saves the chat session locally as and when the chat is progressing and inturn at a later time when you
open SimpleChat, option is provided to restore the old chat session, if a matching one exists.
The UI follows a responsive web design so that the layout can adapt to available display space in a usable
enough manner, in general.
Allows developer/end-user to control some of the behaviour by updating gMe members from browser's devel-tool
console. Parallely some of the directly useful to end-user settings can also be changed using the provided
settings ui.
NOTE: Current web service api doesnt expose the model context length directly, so client logic doesnt provide
any adaptive culling of old messages nor of replacing them with summary of their content etal. However there
is a optional sliding window based chat logic, which provides a simple minded culling of old messages from
the chat history before sending to the ai model.
NOTE: Wrt options sent with the request, it mainly sets temperature, max_tokens and optionaly stream for now.
However if someone wants they can update the js file or equivalent member in gMe as needed.
NOTE: One may be able to use this to chat with openai api web-service /chat/completions endpoint, in a very
limited / minimal way. One will need to set model, openai url and authorization bearer key in settings ui.
## usage
One could run this web frontend directly using server itself or if anyone is thinking of adding a built in web
frontend to configure the server over http(s) or so, then run this web frontend using something like python's
http module.
### running using tools/server
./llama-server -m path/model.gguf --path tools/server/public_simplechat [--port PORT]
### running using python3's server module
first run tools/server
* ./llama-server -m path/model.gguf
next run this web front end in tools/server/public_simplechat
* cd ../tools/server/public_simplechat
* python3 -m http.server PORT
### using the front end
Open this simple web front end from your local browser
* http://127.0.0.1:PORT/index.html
Once inside
* If you want to, you can change many of the default global settings
* the base url (ie ip addr / domain name, port)
* chat (default) vs completion mode
* try trim garbage in response or not
* amount of chat history in the context sent to server/ai-model
* oneshot or streamed mode.
* In completion mode
* one normally doesnt use a system prompt in completion mode.
* logic by default doesnt insert any role specific "ROLE: " prefix wrt each role's message.
If the model requires any prefix wrt user role messages, then the end user has to
explicitly add the needed prefix, when they enter their chat message.
Similarly if the model requires any prefix to trigger assistant/ai-model response,
then the end user needs to enter the same.
This keeps the logic simple, while still giving flexibility to the end user to
manage any templating/tagging requirement wrt their messages to the model.
* the logic doesnt insert newline at the begining and end wrt the prompt message generated.
However if the chat being sent to /completions end point has more than one role's message,
then insert newline when moving from one role's message to the next role's message, so
that it can be clearly identified/distinguished.
* given that /completions endpoint normally doesnt add additional chat-templating of its
own, the above ensures that end user can create a custom single/multi message combo with
any tags/special-tokens related chat templating to test out model handshake. Or enduser
can use it just for normal completion related/based query.
* If you want to provide a system prompt, then ideally enter it first, before entering any user query.
Normally Completion mode doesnt need system prompt, while Chat mode can generate better/interesting
responses with a suitable system prompt.
* if chat.add_system_begin is used
* you cant change the system prompt, after it is has been submitted once along with user query.
* you cant set a system prompt, after you have submitted any user query
* if chat.add_system_anytime is used
* one can change the system prompt any time during chat, by changing the contents of system prompt.
* inturn the updated/changed system prompt will be inserted into the chat session.
* this allows for the subsequent user chatting to be driven by the new system prompt set above.
* Enter your query and either press enter or click on the submit button.
If you want to insert enter (\n) as part of your chat/query to ai model, use shift+enter.
* Wait for the logic to communicate with the server and get the response.
* the user is not allowed to enter any fresh query during this time.
* the user input box will be disabled and a working message will be shown in it.
* if trim garbage is enabled, the logic will try to trim repeating text kind of garbage to some extent.
* just refresh the page, to reset wrt the chat history and or system prompt and start afresh.
* Using NewChat one can start independent chat sessions.
* two independent chat sessions are setup by default.
* When you want to print, switching ChatHistoryInCtxt to Full and clicking on the chat session button of
interest, will display the full chat history till then wrt same, if you want full history for printing.
## Devel note
### Reason behind this
The idea is to be easy enough to use for basic purposes, while also being simple and easily discernable
by developers who may not be from web frontend background (so inturn may not be familiar with template /
end-use-specific-language-extensions driven flows) so that they can use it to explore/experiment things.
And given that the idea is also to help explore/experiment for developers, some flexibility is provided
to change behaviour easily using the devel-tools/console or provided minimal settings ui (wrt few aspects).
Skeletal logic has been implemented to explore some of the end points and ideas/implications around them.
### General
Me/gMe consolidates the settings which control the behaviour into one object.
One can see the current settings, as well as change/update them using browsers devel-tool/console.
It is attached to the document object. Some of these can also be updated using the Settings UI.
baseURL - the domain-name/ip-address and inturn the port to send the request.
bStream - control between oneshot-at-end and live-stream-as-its-generated collating and showing
of the generated response.
the logic assumes that the text sent from the server follows utf-8 encoding.
in streaming mode - if there is any exception, the logic traps the same and tries to ensure
that text generated till then is not lost.
if a very long text is being generated, which leads to no user interaction for sometime and
inturn the machine goes into power saving mode or so, the platform may stop network connection,
leading to exception.
apiEP - select between /completions and /chat/completions endpoint provided by the server/ai-model.
bCompletionFreshChatAlways - whether Completion mode collates complete/sliding-window history when
communicating with the server or only sends the latest user query/message.
bCompletionInsertStandardRolePrefix - whether Completion mode inserts role related prefix wrt the
messages that get inserted into prompt field wrt /Completion endpoint.
bTrimGarbage - whether garbage repeatation at the end of the generated ai response, should be
trimmed or left as is. If enabled, it will be trimmed so that it wont be sent back as part of
subsequent chat history. At the same time the actual trimmed text is shown to the user, once
when it was generated, so user can check if any useful info/data was there in the response.
One may be able to request the ai-model to continue (wrt the last response) (if chat-history
is enabled as part of the chat-history-in-context setting), and chances are the ai-model will
continue starting from the trimmed part, thus allows long response to be recovered/continued
indirectly, in many cases.
The histogram/freq based trimming logic is currently tuned for english language wrt its
is-it-a-alpabetic|numeral-char regex match logic.
apiRequestOptions - maintains the list of options/fields to send along with api request,
irrespective of whether /chat/completions or /completions endpoint.
If you want to add additional options/fields to send to the server/ai-model, and or
modify the existing options value or remove them, for now you can update this global var
using browser's development-tools/console.
For string, numeric and boolean fields in apiRequestOptions, including even those added by a
user at runtime by directly modifying gMe.apiRequestOptions, setting ui entries will be auto
created.
cache_prompt option supported by example/server is allowed to be controlled by user, so that
any caching supported wrt system-prompt and chat history, if usable can get used. When chat
history sliding window is enabled, cache_prompt logic may or may not kick in at the backend
wrt same, based on aspects related to model, positional encoding, attention mechanism etal.
However system prompt should ideally get the benefit of caching.
headers - maintains the list of http headers sent when request is made to the server. By default
Content-Type is set to application/json. Additionally Authorization entry is provided, which can
be set if needed using the settings ui.
iRecentUserMsgCnt - a simple minded SlidingWindow to limit context window load at Ai Model end.
This is disabled by default. However if enabled, then in addition to latest system message, only
the last/latest iRecentUserMsgCnt user messages after the latest system prompt and its responses
from the ai model will be sent to the ai-model, when querying for a new response. IE if enabled,
only user messages after the latest system message/prompt will be considered.
This specified sliding window user message count also includes the latest user query.
<0 : Send entire chat history to server
0 : Send only the system message if any to the server
>0 : Send the latest chat history from the latest system prompt, limited to specified cnt.
By using gMe's iRecentUserMsgCnt and apiRequestOptions.max_tokens/n_predict one can try to control
the implications of loading of the ai-model's context window by chat history, wrt chat response to
some extent in a simple crude way. You may also want to control the context size enabled when the
server loads ai-model, on the server end.
Sometimes the browser may be stuborn with caching of the file, so your updates to html/css/js
may not be visible. Also remember that just refreshing/reloading page in browser or for that
matter clearing site data, dont directly override site caching in all cases. Worst case you may
have to change port. Or in dev tools of browser, you may be able to disable caching fully.
Currently the server to communicate with is maintained globally and not as part of a specific
chat session. So if one changes the server ip/url in setting, then all chat sessions will auto
switch to this new server, when you try using those sessions.
By switching between chat.add_system_begin/anytime, one can control whether one can change
the system prompt, anytime during the conversation or only at the beginning.
### Default setup
By default things are setup to try and make the user experience a bit better, if possible.
However a developer when testing the server of ai-model may want to change these value.
Using iRecentUserMsgCnt reduce chat history context sent to the server/ai-model to be
just the system-prompt, prev-user-request-and-ai-response and cur-user-request, instead of
full chat history. This way if there is any response with garbage/repeatation, it doesnt
mess with things beyond the next question/request/query, in some ways. The trim garbage
option also tries to help avoid issues with garbage in the context to an extent.
Set max_tokens to 1024, so that a relatively large previous reponse doesnt eat up the space
available wrt next query-response. However dont forget that the server when started should
also be started with a model context size of 1k or more, to be on safe side.
The /completions endpoint of tools/server doesnt take max_tokens, instead it takes the
internal n_predict, for now add the same here on the client side, maybe later add max_tokens
to /completions endpoint handling code on server side.
NOTE: One may want to experiment with frequency/presence penalty fields in apiRequestOptions
wrt the set of fields sent to server along with the user query, to check how the model behaves
wrt repeatations in general in the generated text response.
A end-user can change these behaviour by editing gMe from browser's devel-tool/console or by
using the provided settings ui (for settings exposed through the ui).
### OpenAi / Equivalent API WebService
One may be abe to handshake with OpenAI/Equivalent api web service's /chat/completions endpoint
for a minimal chatting experimentation by setting the below.
* the baseUrl in settings ui
* https://api.openai.com/v1 or similar
* Wrt request body - gMe.apiRequestOptions
* model (settings ui)
* any additional fields if required in future
* Wrt request headers - gMe.headers
* Authorization (available through settings ui)
* Bearer THE_OPENAI_API_KEY
* any additional optional header entries like "OpenAI-Organization", "OpenAI-Project" or so
NOTE: Not tested, as there is no free tier api testing available. However logically this might
work.
## At the end
Also a thank you to all open source and open model developers, who strive for the common good.

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/**
* the styling of the simplechat web frontend
* by Humans for All
*/
#fullbody {
height: 98vh;
}
.heading {
background-color: lightgray;
}
.session-selected {
background-color: lightblue;
}
.role-system {
background-color: lightblue;
}
.role-user {
background-color: lightgray;
}
.role-trim {
background-color: lightpink;
}
.gridx2 {
display: grid;
grid-template-columns: repeat(2, 1fr);
border-bottom-style: dotted;
border-bottom-width: thin;
border-bottom-color: lightblue;
}
.flex-grow {
flex-grow: 1;
}
.float-right {
float: right;
}
#chat-div {
overflow: scroll;
flex-grow: 1;
flex-shrink: 1;
min-height: 40vh;
}
button {
min-width: 8vw;
}
.sameline {
display: flex;
flex-direction: row;
}
.samecolumn {
display: flex;
flex-direction: column;
}
.ul1 {
padding-inline-start: 2vw;
}
.ul2 {
padding-inline-start: 2vw;
}
* {
margin: 0.6vmin;
}
@media print {
#fullbody {
height: auto;
}
}

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// @ts-check
// A simple completions and chat/completions test related web front end logic
// by Humans for All
import * as du from "./datautils.mjs";
import * as ui from "./ui.mjs"
class Roles {
static System = "system";
static User = "user";
static Assistant = "assistant";
}
class ApiEP {
static Type = {
Chat: "chat",
Completion: "completion",
}
static UrlSuffix = {
'chat': `/chat/completions`,
'completion': `/completions`,
}
/**
* Build the url from given baseUrl and apiEp id.
* @param {string} baseUrl
* @param {string} apiEP
*/
static Url(baseUrl, apiEP) {
if (baseUrl.endsWith("/")) {
baseUrl = baseUrl.substring(0, baseUrl.length-1);
}
return `${baseUrl}${this.UrlSuffix[apiEP]}`;
}
}
let gUsageMsg = `
<p class="role-system">Usage</p>
<ul class="ul1">
<li> System prompt above, to try control ai response characteristics.</li>
<ul class="ul2">
<li> Completion mode - no system prompt normally.</li>
</ul>
<li> Use shift+enter for inserting enter/newline.</li>
<li> Enter your query to ai assistant below.</li>
<li> Default ContextWindow = [System, Last Query+Resp, Cur Query].</li>
<ul class="ul2">
<li> ChatHistInCtxt, MaxTokens, ModelCtxt window to expand</li>
</ul>
</ul>
`;
/** @typedef {{role: string, content: string}[]} ChatMessages */
/** @typedef {{iLastSys: number, xchat: ChatMessages}} SimpleChatODS */
class SimpleChat {
/**
* @param {string} chatId
*/
constructor(chatId) {
this.chatId = chatId;
/**
* Maintain in a form suitable for common LLM web service chat/completions' messages entry
* @type {ChatMessages}
*/
this.xchat = [];
this.iLastSys = -1;
this.latestResponse = "";
}
clear() {
this.xchat = [];
this.iLastSys = -1;
}
ods_key() {
return `SimpleChat-${this.chatId}`
}
save() {
/** @type {SimpleChatODS} */
let ods = {iLastSys: this.iLastSys, xchat: this.xchat};
localStorage.setItem(this.ods_key(), JSON.stringify(ods));
}
load() {
let sods = localStorage.getItem(this.ods_key());
if (sods == null) {
return;
}
/** @type {SimpleChatODS} */
let ods = JSON.parse(sods);
this.iLastSys = ods.iLastSys;
this.xchat = ods.xchat;
}
/**
* Recent chat messages.
* If iRecentUserMsgCnt < 0
* Then return the full chat history
* Else
* Return chat messages from latest going back till the last/latest system prompt.
* While keeping track that the number of user queries/messages doesnt exceed iRecentUserMsgCnt.
* @param {number} iRecentUserMsgCnt
*/
recent_chat(iRecentUserMsgCnt) {
if (iRecentUserMsgCnt < 0) {
return this.xchat;
}
if (iRecentUserMsgCnt == 0) {
console.warn("WARN:SimpleChat:SC:RecentChat:iRecentUsermsgCnt of 0 means no user message/query sent");
}
/** @type{ChatMessages} */
let rchat = [];
let sysMsg = this.get_system_latest();
if (sysMsg.length != 0) {
rchat.push({role: Roles.System, content: sysMsg});
}
let iUserCnt = 0;
let iStart = this.xchat.length;
for(let i=this.xchat.length-1; i > this.iLastSys; i--) {
if (iUserCnt >= iRecentUserMsgCnt) {
break;
}
let msg = this.xchat[i];
if (msg.role == Roles.User) {
iStart = i;
iUserCnt += 1;
}
}
for(let i = iStart; i < this.xchat.length; i++) {
let msg = this.xchat[i];
if (msg.role == Roles.System) {
continue;
}
rchat.push({role: msg.role, content: msg.content});
}
return rchat;
}
/**
* Collate the latest response from the server/ai-model, as it is becoming available.
* This is mainly useful for the stream mode.
* @param {string} content
*/
append_response(content) {
this.latestResponse += content;
}
/**
* Add an entry into xchat
* @param {string} role
* @param {string|undefined|null} content
*/
add(role, content) {
if ((content == undefined) || (content == null) || (content == "")) {
return false;
}
this.xchat.push( {role: role, content: content} );
if (role == Roles.System) {
this.iLastSys = this.xchat.length - 1;
}
this.save();
return true;
}
/**
* Show the contents in the specified div
* @param {HTMLDivElement} div
* @param {boolean} bClear
*/
show(div, bClear=true) {
if (bClear) {
div.replaceChildren();
}
let last = undefined;
for(const x of this.recent_chat(gMe.iRecentUserMsgCnt)) {
let entry = ui.el_create_append_p(`${x.role}: ${x.content}`, div);
entry.className = `role-${x.role}`;
last = entry;
}
if (last !== undefined) {
last.scrollIntoView(false);
} else {
if (bClear) {
div.innerHTML = gUsageMsg;
gMe.setup_load(div, this);
gMe.show_info(div);
}
}
return last;
}
/**
* Setup the fetch headers.
* It picks the headers from gMe.headers.
* It inserts Authorization only if its non-empty.
* @param {string} apiEP
*/
fetch_headers(apiEP) {
let headers = new Headers();
for(let k in gMe.headers) {
let v = gMe.headers[k];
if ((k == "Authorization") && (v.trim() == "")) {
continue;
}
headers.append(k, v);
}
return headers;
}
/**
* Add needed fields wrt json object to be sent wrt LLM web services completions endpoint.
* The needed fields/options are picked from a global object.
* Add optional stream flag, if required.
* Convert the json into string.
* @param {Object} obj
*/
request_jsonstr_extend(obj) {
for(let k in gMe.apiRequestOptions) {
obj[k] = gMe.apiRequestOptions[k];
}
if (gMe.bStream) {
obj["stream"] = true;
}
return JSON.stringify(obj);
}
/**
* Return a string form of json object suitable for chat/completions
*/
request_messages_jsonstr() {
let req = {
messages: this.recent_chat(gMe.iRecentUserMsgCnt),
}
return this.request_jsonstr_extend(req);
}
/**
* Return a string form of json object suitable for /completions
* @param {boolean} bInsertStandardRolePrefix Insert "<THE_ROLE>: " as prefix wrt each role's message
*/
request_prompt_jsonstr(bInsertStandardRolePrefix) {
let prompt = "";
let iCnt = 0;
for(const chat of this.recent_chat(gMe.iRecentUserMsgCnt)) {
iCnt += 1;
if (iCnt > 1) {
prompt += "\n";
}
if (bInsertStandardRolePrefix) {
prompt += `${chat.role}: `;
}
prompt += `${chat.content}`;
}
let req = {
prompt: prompt,
}
return this.request_jsonstr_extend(req);
}
/**
* Return a string form of json object suitable for specified api endpoint.
* @param {string} apiEP
*/
request_jsonstr(apiEP) {
if (apiEP == ApiEP.Type.Chat) {
return this.request_messages_jsonstr();
} else {
return this.request_prompt_jsonstr(gMe.bCompletionInsertStandardRolePrefix);
}
}
/**
* Extract the ai-model/assistant's response from the http response got.
* Optionally trim the message wrt any garbage at the end.
* @param {any} respBody
* @param {string} apiEP
*/
response_extract(respBody, apiEP) {
let assistant = "";
if (apiEP == ApiEP.Type.Chat) {
assistant = respBody["choices"][0]["message"]["content"];
} else {
try {
assistant = respBody["choices"][0]["text"];
} catch {
assistant = respBody["content"];
}
}
return assistant;
}
/**
* Extract the ai-model/assistant's response from the http response got in streaming mode.
* @param {any} respBody
* @param {string} apiEP
*/
response_extract_stream(respBody, apiEP) {
let assistant = "";
if (apiEP == ApiEP.Type.Chat) {
if (respBody["choices"][0]["finish_reason"] !== "stop") {
assistant = respBody["choices"][0]["delta"]["content"];
}
} else {
try {
assistant = respBody["choices"][0]["text"];
} catch {
assistant = respBody["content"];
}
}
return assistant;
}
/**
* Allow setting of system prompt, but only at begining.
* @param {string} sysPrompt
* @param {string} msgTag
*/
add_system_begin(sysPrompt, msgTag) {
if (this.xchat.length == 0) {
if (sysPrompt.length > 0) {
return this.add(Roles.System, sysPrompt);
}
} else {
if (sysPrompt.length > 0) {
if (this.xchat[0].role !== Roles.System) {
console.error(`ERRR:SimpleChat:SC:${msgTag}:You need to specify system prompt before any user query, ignoring...`);
} else {
if (this.xchat[0].content !== sysPrompt) {
console.error(`ERRR:SimpleChat:SC:${msgTag}:You cant change system prompt, mid way through, ignoring...`);
}
}
}
}
return false;
}
/**
* Allow setting of system prompt, at any time.
* @param {string} sysPrompt
* @param {string} msgTag
*/
add_system_anytime(sysPrompt, msgTag) {
if (sysPrompt.length <= 0) {
return false;
}
if (this.iLastSys < 0) {
return this.add(Roles.System, sysPrompt);
}
let lastSys = this.xchat[this.iLastSys].content;
if (lastSys !== sysPrompt) {
return this.add(Roles.System, sysPrompt);
}
return false;
}
/**
* Retrieve the latest system prompt.
*/
get_system_latest() {
if (this.iLastSys == -1) {
return "";
}
let sysPrompt = this.xchat[this.iLastSys].content;
return sysPrompt;
}
/**
* Handle the multipart response from server/ai-model
* @param {Response} resp
* @param {string} apiEP
* @param {HTMLDivElement} elDiv
*/
async handle_response_multipart(resp, apiEP, elDiv) {
let elP = ui.el_create_append_p("", elDiv);
if (!resp.body) {
throw Error("ERRR:SimpleChat:SC:HandleResponseMultiPart:No body...");
}
let tdUtf8 = new TextDecoder("utf-8");
let rr = resp.body.getReader();
this.latestResponse = "";
let xLines = new du.NewLines();
while(true) {
let { value: cur, done: done } = await rr.read();
if (cur) {
let curBody = tdUtf8.decode(cur, {stream: true});
console.debug("DBUG:SC:PART:Str:", curBody);
xLines.add_append(curBody);
}
while(true) {
let curLine = xLines.shift(!done);
if (curLine == undefined) {
break;
}
if (curLine.trim() == "") {
continue;
}
if (curLine.startsWith("data:")) {
curLine = curLine.substring(5);
}
if (curLine.trim() === "[DONE]") {
break;
}
let curJson = JSON.parse(curLine);
console.debug("DBUG:SC:PART:Json:", curJson);
this.append_response(this.response_extract_stream(curJson, apiEP));
}
elP.innerText = this.latestResponse;
elP.scrollIntoView(false);
if (done) {
break;
}
}
console.debug("DBUG:SC:PART:Full:", this.latestResponse);
return this.latestResponse;
}
/**
* Handle the oneshot response from server/ai-model
* @param {Response} resp
* @param {string} apiEP
*/
async handle_response_oneshot(resp, apiEP) {
let respBody = await resp.json();
console.debug(`DBUG:SimpleChat:SC:${this.chatId}:HandleUserSubmit:RespBody:${JSON.stringify(respBody)}`);
return this.response_extract(respBody, apiEP);
}
/**
* Handle the response from the server be it in oneshot or multipart/stream mode.
* Also take care of the optional garbage trimming.
* @param {Response} resp
* @param {string} apiEP
* @param {HTMLDivElement} elDiv
*/
async handle_response(resp, apiEP, elDiv) {
let theResp = {
assistant: "",
trimmed: "",
}
if (gMe.bStream) {
try {
theResp.assistant = await this.handle_response_multipart(resp, apiEP, elDiv);
this.latestResponse = "";
} catch (error) {
theResp.assistant = this.latestResponse;
this.add(Roles.Assistant, theResp.assistant);
this.latestResponse = "";
throw error;
}
} else {
theResp.assistant = await this.handle_response_oneshot(resp, apiEP);
}
if (gMe.bTrimGarbage) {
let origMsg = theResp.assistant;
theResp.assistant = du.trim_garbage_at_end(origMsg);
theResp.trimmed = origMsg.substring(theResp.assistant.length);
}
this.add(Roles.Assistant, theResp.assistant);
return theResp;
}
}
class MultiChatUI {
constructor() {
/** @type {Object<string, SimpleChat>} */
this.simpleChats = {};
/** @type {string} */
this.curChatId = "";
// the ui elements
this.elInSystem = /** @type{HTMLInputElement} */(document.getElementById("system-in"));
this.elDivChat = /** @type{HTMLDivElement} */(document.getElementById("chat-div"));
this.elBtnUser = /** @type{HTMLButtonElement} */(document.getElementById("user-btn"));
this.elInUser = /** @type{HTMLInputElement} */(document.getElementById("user-in"));
this.elDivHeading = /** @type{HTMLSelectElement} */(document.getElementById("heading"));
this.elDivSessions = /** @type{HTMLDivElement} */(document.getElementById("sessions-div"));
this.elBtnSettings = /** @type{HTMLButtonElement} */(document.getElementById("settings"));
this.validate_element(this.elInSystem, "system-in");
this.validate_element(this.elDivChat, "chat-div");
this.validate_element(this.elInUser, "user-in");
this.validate_element(this.elDivHeading, "heading");
this.validate_element(this.elDivChat, "sessions-div");
this.validate_element(this.elBtnSettings, "settings");
}
/**
* Check if the element got
* @param {HTMLElement | null} el
* @param {string} msgTag
*/
validate_element(el, msgTag) {
if (el == null) {
throw Error(`ERRR:SimpleChat:MCUI:${msgTag} element missing in html...`);
} else {
console.debug(`INFO:SimpleChat:MCUI:${msgTag} Id[${el.id}] Name[${el["name"]}]`);
}
}
/**
* Reset user input ui.
* * clear user input
* * enable user input
* * set focus to user input
*/
ui_reset_userinput() {
this.elInUser.value = "";
this.elInUser.disabled = false;
this.elInUser.focus();
}
/**
* Setup the needed callbacks wrt UI, curChatId to defaultChatId and
* optionally switch to specified defaultChatId.
* @param {string} defaultChatId
* @param {boolean} bSwitchSession
*/
setup_ui(defaultChatId, bSwitchSession=false) {
this.curChatId = defaultChatId;
if (bSwitchSession) {
this.handle_session_switch(this.curChatId);
}
this.elBtnSettings.addEventListener("click", (ev)=>{
this.elDivChat.replaceChildren();
gMe.show_settings(this.elDivChat);
});
this.elBtnUser.addEventListener("click", (ev)=>{
if (this.elInUser.disabled) {
return;
}
this.handle_user_submit(this.curChatId, gMe.apiEP).catch((/** @type{Error} */reason)=>{
let msg = `ERRR:SimpleChat\nMCUI:HandleUserSubmit:${this.curChatId}\n${reason.name}:${reason.message}`;
console.error(msg.replace("\n", ":"));
alert(msg);
this.ui_reset_userinput();
});
});
this.elInUser.addEventListener("keyup", (ev)=> {
// allow user to insert enter into their message using shift+enter.
// while just pressing enter key will lead to submitting.
if ((ev.key === "Enter") && (!ev.shiftKey)) {
let value = this.elInUser.value;
this.elInUser.value = value.substring(0,value.length-1);
this.elBtnUser.click();
ev.preventDefault();
}
});
this.elInSystem.addEventListener("keyup", (ev)=> {
// allow user to insert enter into the system prompt using shift+enter.
// while just pressing enter key will lead to setting the system prompt.
if ((ev.key === "Enter") && (!ev.shiftKey)) {
let value = this.elInSystem.value;
this.elInSystem.value = value.substring(0,value.length-1);
let chat = this.simpleChats[this.curChatId];
chat.add_system_anytime(this.elInSystem.value, this.curChatId);
chat.show(this.elDivChat);
ev.preventDefault();
}
});
}
/**
* Setup a new chat session and optionally switch to it.
* @param {string} chatId
* @param {boolean} bSwitchSession
*/
new_chat_session(chatId, bSwitchSession=false) {
this.simpleChats[chatId] = new SimpleChat(chatId);
if (bSwitchSession) {
this.handle_session_switch(chatId);
}
}
/**
* Handle user query submit request, wrt specified chat session.
* @param {string} chatId
* @param {string} apiEP
*/
async handle_user_submit(chatId, apiEP) {
let chat = this.simpleChats[chatId];
// In completion mode, if configured, clear any previous chat history.
// So if user wants to simulate a multi-chat based completion query,
// they will have to enter the full thing, as a suitable multiline
// user input/query.
if ((apiEP == ApiEP.Type.Completion) && (gMe.bCompletionFreshChatAlways)) {
chat.clear();
}
chat.add_system_anytime(this.elInSystem.value, chatId);
let content = this.elInUser.value;
if (!chat.add(Roles.User, content)) {
console.debug(`WARN:SimpleChat:MCUI:${chatId}:HandleUserSubmit:Ignoring empty user input...`);
return;
}
chat.show(this.elDivChat);
let theUrl = ApiEP.Url(gMe.baseURL, apiEP);
let theBody = chat.request_jsonstr(apiEP);
this.elInUser.value = "working...";
this.elInUser.disabled = true;
console.debug(`DBUG:SimpleChat:MCUI:${chatId}:HandleUserSubmit:${theUrl}:ReqBody:${theBody}`);
let theHeaders = chat.fetch_headers(apiEP);
let resp = await fetch(theUrl, {
method: "POST",
headers: theHeaders,
body: theBody,
});
let theResp = await chat.handle_response(resp, apiEP, this.elDivChat);
if (chatId == this.curChatId) {
chat.show(this.elDivChat);
if (theResp.trimmed.length > 0) {
let p = ui.el_create_append_p(`TRIMMED:${theResp.trimmed}`, this.elDivChat);
p.className="role-trim";
}
} else {
console.debug(`DBUG:SimpleChat:MCUI:HandleUserSubmit:ChatId has changed:[${chatId}] [${this.curChatId}]`);
}
this.ui_reset_userinput();
}
/**
* Show buttons for NewChat and available chat sessions, in the passed elDiv.
* If elDiv is undefined/null, then use this.elDivSessions.
* Take care of highlighting the selected chat-session's btn.
* @param {HTMLDivElement | undefined} elDiv
*/
show_sessions(elDiv=undefined) {
if (!elDiv) {
elDiv = this.elDivSessions;
}
elDiv.replaceChildren();
// Btn for creating new chat session
let btnNew = ui.el_create_button("New CHAT", (ev)=> {
if (this.elInUser.disabled) {
console.error(`ERRR:SimpleChat:MCUI:NewChat:Current session [${this.curChatId}] awaiting response, ignoring request...`);
alert("ERRR:SimpleChat\nMCUI:NewChat\nWait for response to pending query, before starting new chat session");
return;
}
let chatId = `Chat${Object.keys(this.simpleChats).length}`;
let chatIdGot = prompt("INFO:SimpleChat\nMCUI:NewChat\nEnter id for new chat session", chatId);
if (!chatIdGot) {
console.error("ERRR:SimpleChat:MCUI:NewChat:Skipping based on user request...");
return;
}
this.new_chat_session(chatIdGot, true);
this.create_session_btn(elDiv, chatIdGot);
ui.el_children_config_class(elDiv, chatIdGot, "session-selected", "");
});
elDiv.appendChild(btnNew);
// Btns for existing chat sessions
let chatIds = Object.keys(this.simpleChats);
for(let cid of chatIds) {
let btn = this.create_session_btn(elDiv, cid);
if (cid == this.curChatId) {
btn.className = "session-selected";
}
}
}
create_session_btn(elDiv, cid) {
let btn = ui.el_create_button(cid, (ev)=>{
let target = /** @type{HTMLButtonElement} */(ev.target);
console.debug(`DBUG:SimpleChat:MCUI:SessionClick:${target.id}`);
if (this.elInUser.disabled) {
console.error(`ERRR:SimpleChat:MCUI:SessionClick:${target.id}:Current session [${this.curChatId}] awaiting response, ignoring switch...`);
alert("ERRR:SimpleChat\nMCUI:SessionClick\nWait for response to pending query, before switching");
return;
}
this.handle_session_switch(target.id);
ui.el_children_config_class(elDiv, target.id, "session-selected", "");
});
elDiv.appendChild(btn);
return btn;
}
/**
* Switch ui to the specified chatId and set curChatId to same.
* @param {string} chatId
*/
async handle_session_switch(chatId) {
let chat = this.simpleChats[chatId];
if (chat == undefined) {
console.error(`ERRR:SimpleChat:MCUI:HandleSessionSwitch:${chatId} missing...`);
return;
}
this.elInSystem.value = chat.get_system_latest();
this.elInUser.value = "";
chat.show(this.elDivChat);
this.elInUser.focus();
this.curChatId = chatId;
console.log(`INFO:SimpleChat:MCUI:HandleSessionSwitch:${chatId} entered...`);
}
}
class Me {
constructor() {
this.baseURL = "http://127.0.0.1:8080";
this.defaultChatIds = [ "Default", "Other" ];
this.multiChat = new MultiChatUI();
this.bStream = true;
this.bCompletionFreshChatAlways = true;
this.bCompletionInsertStandardRolePrefix = false;
this.bTrimGarbage = true;
this.iRecentUserMsgCnt = 2;
this.sRecentUserMsgCnt = {
"Full": -1,
"Last0": 1,
"Last1": 2,
"Last2": 3,
"Last4": 5,
};
this.apiEP = ApiEP.Type.Chat;
this.headers = {
"Content-Type": "application/json",
"Authorization": "", // Authorization: Bearer OPENAI_API_KEY
}
// Add needed fields wrt json object to be sent wrt LLM web services completions endpoint.
this.apiRequestOptions = {
"model": "gpt-3.5-turbo",
"temperature": 0.7,
"max_tokens": 1024,
"n_predict": 1024,
"cache_prompt": false,
//"frequency_penalty": 1.2,
//"presence_penalty": 1.2,
};
}
/**
* Disable console.debug by mapping it to a empty function.
*/
debug_disable() {
this.console_debug = console.debug;
console.debug = () => {
};
}
/**
* Setup the load saved chat ui.
* @param {HTMLDivElement} div
* @param {SimpleChat} chat
*/
setup_load(div, chat) {
if (!(chat.ods_key() in localStorage)) {
return;
}
div.innerHTML += `<p class="role-system">Restore</p>
<p>Load previously saved chat session, if available</p>`;
let btn = ui.el_create_button(chat.ods_key(), (ev)=>{
console.log("DBUG:SimpleChat:SC:Load", chat);
chat.load();
queueMicrotask(()=>{
chat.show(div);
this.multiChat.elInSystem.value = chat.get_system_latest();
});
});
div.appendChild(btn);
}
/**
* Show the configurable parameters info in the passed Div element.
* @param {HTMLDivElement} elDiv
* @param {boolean} bAll
*/
show_info(elDiv, bAll=false) {
let p = ui.el_create_append_p("Settings (devel-tools-console document[gMe])", elDiv);
p.className = "role-system";
if (bAll) {
ui.el_create_append_p(`baseURL:${this.baseURL}`, elDiv);
ui.el_create_append_p(`Authorization:${this.headers["Authorization"]}`, elDiv);
ui.el_create_append_p(`bStream:${this.bStream}`, elDiv);
ui.el_create_append_p(`bTrimGarbage:${this.bTrimGarbage}`, elDiv);
ui.el_create_append_p(`ApiEndPoint:${this.apiEP}`, elDiv);
ui.el_create_append_p(`iRecentUserMsgCnt:${this.iRecentUserMsgCnt}`, elDiv);
ui.el_create_append_p(`bCompletionFreshChatAlways:${this.bCompletionFreshChatAlways}`, elDiv);
ui.el_create_append_p(`bCompletionInsertStandardRolePrefix:${this.bCompletionInsertStandardRolePrefix}`, elDiv);
}
ui.el_create_append_p(`apiRequestOptions:${JSON.stringify(this.apiRequestOptions, null, " - ")}`, elDiv);
ui.el_create_append_p(`headers:${JSON.stringify(this.headers, null, " - ")}`, elDiv);
}
/**
* Auto create ui input elements for fields in apiRequestOptions
* Currently supports text and number field types.
* @param {HTMLDivElement} elDiv
*/
show_settings_apirequestoptions(elDiv) {
let typeDict = {
"string": "text",
"number": "number",
};
let fs = document.createElement("fieldset");
let legend = document.createElement("legend");
legend.innerText = "ApiRequestOptions";
fs.appendChild(legend);
elDiv.appendChild(fs);
for(const k in this.apiRequestOptions) {
let val = this.apiRequestOptions[k];
let type = typeof(val);
if (((type == "string") || (type == "number"))) {
let inp = ui.el_creatediv_input(`Set${k}`, k, typeDict[type], this.apiRequestOptions[k], (val)=>{
if (type == "number") {
val = Number(val);
}
this.apiRequestOptions[k] = val;
});
fs.appendChild(inp.div);
} else if (type == "boolean") {
let bbtn = ui.el_creatediv_boolbutton(`Set{k}`, k, {true: "true", false: "false"}, val, (userVal)=>{
this.apiRequestOptions[k] = userVal;
});
fs.appendChild(bbtn.div);
}
}
}
/**
* Show settings ui for configurable parameters, in the passed Div element.
* @param {HTMLDivElement} elDiv
*/
show_settings(elDiv) {
let inp = ui.el_creatediv_input("SetBaseURL", "BaseURL", "text", this.baseURL, (val)=>{
this.baseURL = val;
});
elDiv.appendChild(inp.div);
inp = ui.el_creatediv_input("SetAuthorization", "Authorization", "text", this.headers["Authorization"], (val)=>{
this.headers["Authorization"] = val;
});
inp.el.placeholder = "Bearer OPENAI_API_KEY";
elDiv.appendChild(inp.div);
let bb = ui.el_creatediv_boolbutton("SetStream", "Stream", {true: "[+] yes stream", false: "[-] do oneshot"}, this.bStream, (val)=>{
this.bStream = val;
});
elDiv.appendChild(bb.div);
bb = ui.el_creatediv_boolbutton("SetTrimGarbage", "TrimGarbage", {true: "[+] yes trim", false: "[-] dont trim"}, this.bTrimGarbage, (val)=>{
this.bTrimGarbage = val;
});
elDiv.appendChild(bb.div);
this.show_settings_apirequestoptions(elDiv);
let sel = ui.el_creatediv_select("SetApiEP", "ApiEndPoint", ApiEP.Type, this.apiEP, (val)=>{
this.apiEP = ApiEP.Type[val];
});
elDiv.appendChild(sel.div);
sel = ui.el_creatediv_select("SetChatHistoryInCtxt", "ChatHistoryInCtxt", this.sRecentUserMsgCnt, this.iRecentUserMsgCnt, (val)=>{
this.iRecentUserMsgCnt = this.sRecentUserMsgCnt[val];
});
elDiv.appendChild(sel.div);
bb = ui.el_creatediv_boolbutton("SetCompletionFreshChatAlways", "CompletionFreshChatAlways", {true: "[+] yes fresh", false: "[-] no, with history"}, this.bCompletionFreshChatAlways, (val)=>{
this.bCompletionFreshChatAlways = val;
});
elDiv.appendChild(bb.div);
bb = ui.el_creatediv_boolbutton("SetCompletionInsertStandardRolePrefix", "CompletionInsertStandardRolePrefix", {true: "[+] yes insert", false: "[-] dont insert"}, this.bCompletionInsertStandardRolePrefix, (val)=>{
this.bCompletionInsertStandardRolePrefix = val;
});
elDiv.appendChild(bb.div);
}
}
/** @type {Me} */
let gMe;
function startme() {
console.log("INFO:SimpleChat:StartMe:Starting...");
gMe = new Me();
gMe.debug_disable();
document["gMe"] = gMe;
document["du"] = du;
for (let cid of gMe.defaultChatIds) {
gMe.multiChat.new_chat_session(cid);
}
gMe.multiChat.setup_ui(gMe.defaultChatIds[0], true);
gMe.multiChat.show_sessions();
}
document.addEventListener("DOMContentLoaded", startme);

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//@ts-check
// Helpers to work with html elements
// by Humans for All
//
/**
* Set the class of the children, based on whether it is the idSelected or not.
* @param {HTMLDivElement} elBase
* @param {string} idSelected
* @param {string} classSelected
* @param {string} classUnSelected
*/
export function el_children_config_class(elBase, idSelected, classSelected, classUnSelected="") {
for(let child of elBase.children) {
if (child.id == idSelected) {
child.className = classSelected;
} else {
child.className = classUnSelected;
}
}
}
/**
* Create button and set it up.
* @param {string} id
* @param {(this: HTMLButtonElement, ev: MouseEvent) => any} callback
* @param {string | undefined} name
* @param {string | undefined} innerText
*/
export function el_create_button(id, callback, name=undefined, innerText=undefined) {
if (!name) {
name = id;
}
if (!innerText) {
innerText = id;
}
let btn = document.createElement("button");
btn.id = id;
btn.name = name;
btn.innerText = innerText;
btn.addEventListener("click", callback);
return btn;
}
/**
* Create a para and set it up. Optionaly append it to a passed parent.
* @param {string} text
* @param {HTMLElement | undefined} elParent
* @param {string | undefined} id
*/
export function el_create_append_p(text, elParent=undefined, id=undefined) {
let para = document.createElement("p");
para.innerText = text;
if (id) {
para.id = id;
}
if (elParent) {
elParent.appendChild(para);
}
return para;
}
/**
* Create a button which represents bool value using specified text wrt true and false.
* When ever user clicks the button, it will toggle the value and update the shown text.
*
* @param {string} id
* @param {{true: string, false: string}} texts
* @param {boolean} defaultValue
* @param {function(boolean):void} cb
*/
export function el_create_boolbutton(id, texts, defaultValue, cb) {
let el = document.createElement("button");
el["xbool"] = defaultValue;
el["xtexts"] = structuredClone(texts);
el.innerText = el["xtexts"][String(defaultValue)];
if (id) {
el.id = id;
}
el.addEventListener('click', (ev)=>{
el["xbool"] = !el["xbool"];
el.innerText = el["xtexts"][String(el["xbool"])];
cb(el["xbool"]);
})
return el;
}
/**
* Create a div wrapped button which represents bool value using specified text wrt true and false.
* @param {string} id
* @param {string} label
* @param {{ true: string; false: string; }} texts
* @param {boolean} defaultValue
* @param {(arg0: boolean) => void} cb
* @param {string} className
*/
export function el_creatediv_boolbutton(id, label, texts, defaultValue, cb, className="gridx2") {
let div = document.createElement("div");
div.className = className;
let lbl = document.createElement("label");
lbl.setAttribute("for", id);
lbl.innerText = label;
div.appendChild(lbl);
let btn = el_create_boolbutton(id, texts, defaultValue, cb);
div.appendChild(btn);
return { div: div, el: btn };
}
/**
* Create a select ui element, with a set of options to select from.
* * options: an object which contains name-value pairs
* * defaultOption: the value whose name should be choosen, by default.
* * cb : the call back returns the name string of the option selected.
*
* @param {string} id
* @param {Object<string,*>} options
* @param {*} defaultOption
* @param {function(string):void} cb
*/
export function el_create_select(id, options, defaultOption, cb) {
let el = document.createElement("select");
el["xselected"] = defaultOption;
el["xoptions"] = structuredClone(options);
for(let cur of Object.keys(options)) {
let op = document.createElement("option");
op.value = cur;
op.innerText = cur;
if (options[cur] == defaultOption) {
op.selected = true;
}
el.appendChild(op);
}
if (id) {
el.id = id;
el.name = id;
}
el.addEventListener('change', (ev)=>{
let target = /** @type{HTMLSelectElement} */(ev.target);
console.log("DBUG:UI:Select:", id, ":", target.value);
cb(target.value);
})
return el;
}
/**
* Create a div wrapped select ui element, with a set of options to select from.
*
* @param {string} id
* @param {any} label
* @param {{ [x: string]: any; }} options
* @param {any} defaultOption
* @param {(arg0: string) => void} cb
* @param {string} className
*/
export function el_creatediv_select(id, label, options, defaultOption, cb, className="gridx2") {
let div = document.createElement("div");
div.className = className;
let lbl = document.createElement("label");
lbl.setAttribute("for", id);
lbl.innerText = label;
div.appendChild(lbl);
let sel = el_create_select(id, options,defaultOption, cb);
div.appendChild(sel);
return { div: div, el: sel };
}
/**
* Create a input ui element.
*
* @param {string} id
* @param {string} type
* @param {any} defaultValue
* @param {function(any):void} cb
*/
export function el_create_input(id, type, defaultValue, cb) {
let el = document.createElement("input");
el.type = type;
el.value = defaultValue;
if (id) {
el.id = id;
}
el.addEventListener('change', (ev)=>{
cb(el.value);
})
return el;
}
/**
* Create a div wrapped input.
*
* @param {string} id
* @param {string} label
* @param {string} type
* @param {any} defaultValue
* @param {function(any):void} cb
* @param {string} className
*/
export function el_creatediv_input(id, label, type, defaultValue, cb, className="gridx2") {
let div = document.createElement("div");
div.className = className;
let lbl = document.createElement("label");
lbl.setAttribute("for", id);
lbl.innerText = label;
div.appendChild(lbl);
let el = el_create_input(id, type, defaultValue, cb);
div.appendChild(el);
return { div: div, el: el };
}