mirror of https://github.com/ggerganov/llama.cpp.git synced 2024-10-31 23:28:51 +01:00

SimpleChat Completion Mode flexibility and cleanup, Settings gMe, Optional sliding window (#7480 )

* SimpleChat: A placeholder system prompt, Use usage msg in code

Just have a alert msg wrt needing javascript enabled in html. And
have usage message from js file. Update the usage message a bit.
So also enable switch session wrt setup_ui call.

Add a possible system prompt as a placeholder for the system-input.

* SimpleChat:CompletionMode: Allow control of Role: prefix

* SimpleChat:Completion: Avoid Role: prefix; Newline only in between

In completion mode

* avoid inserting Role: prefix before each role's message

* avoid inserting newline at the begin and end of the prompt
  message. However if there are multiple role messages, then
  insert newline when going from one role's message to the
  next role's message.

* SimpleChat:CompletionMode: Update readme/usage, trim textarea newline

Readme update wrt completion mode behavior.

Usage help updated wrt completion mode behavior.

When changing from input to textarea elment wrt user input, the last
newline at the end of the user input wrt textarea, was forgotten to be
filtered, this is fixed now. However if user wants to have a explicit
newline they can using shift+enter to insert a newline, that wont be
removed. The extra newline removal logic uses substring and keyup to
keep things simple and avoid some previously noted bugs wrt other
events in the key path as well as IME composition etal.

* SimpleChat:SC: Ensure proper clearing/reseting

previous logic would have cleared/reset the xchat, without doing
the same wrt iLastSys, thus leading to it pointing to a now non
existent role-content entry.

So if a user set a system prompt and used completion mode, it would
have done the half stupid clear, after the model response was got.
Inturn when user tries to send a new completion query, it would
inturn lead to handle_user_submit trying to add/update system prompt
if any, which will fail, bcas iLastSys will be still pointing to a
non existant entry.

This is fixed now, by having a proper clear helper wrt SC class.

* SimpleChat: Update usage note and readme a bit

* SimpleChat:Completion: clear any prev chat history at begining

Previously any chat history including model response to a completion
query would have got cleared, after showing the same to the user,
at the end of handle_user_submit, rather than at the begining.

This gave the flexibility that user could switch from chat mode
to completion mode and have the chat history till then sent to
the ai model, as part of the completion query. However this flow
also had the issue that, if user switches between different chat
sessions, after getting a completion response, they can no longer
see the completion query and its response that they had just got.

The new flow changes the clearing of chat history wrt completion
mode to the begining of handle_user_submit, so that user doesnt
lose the last completion mode query and response, till a new
completion mode query is sent to the model, even if they were to
switch between the chat sessions. At the same time the loss of
flexibility wrt converting previous chat history into being part
of the completion query implicitly doesnt matter, because now
the end user can enter multiline queries.

* SimpleChat:Try read json early, if available

For later

the server flow doesnt seem to be sending back data early, atleast
for the request (inc options) that is currently sent.

if able to read json data early on in future, as and when ai model
is generating data, then this helper needs to indirectly update
the chat div with the recieved data, without waiting for the
overall data to be available.

* SimpleChat: Rename the half asleep mis-spelled global var

* SimpleChat: Common chat request options from a global object

* SimpleChat: Update title, usage and readme a bit

Keep the title simple so that print file name doesnt have chars
that need to be removed.

Update readme wrt some of the new helpers and options.

Change Usage list to a list of lists, add few items and style it
to reduce the margin wrt lists.

* SimpleChat:ChatRequestOptions: max_tokens

As some times based on the query from the user, the ai model may get
into a run away kind of generation with repeatations etal, so adding
max_tokens to try and limit this run away behaviour, if possible.

* SimpleChat: Reduce max_tokens to be small but still sufficient

* SimpleChat: Consolidate global vars into gMe, Display to user

This allows the end user to see the settings used by the logic,
as well as allows users to change/update the settings if they
want to by using devel-tools/console

* SimpleChat:SlidingWindow: iRecentUserMsgCnt to limit context load

This is disabled by default. However if enabled, then in addition
to latest system message, only the last N user messages, after the
latest system message and its reponses from the ai model will be sent
to the ai-model, when querying for a new response.

This specified N also includes the latest user query.

* SimpleChat: placeholder based usage hint for user-in textarea

* SimpleChat: Try make user experience better, if possible

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 the previous full chat history.
This way if there is any response with garbage/repeatation, it
doesnt mess with things beyond the next question, in some ways.

Increase 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.

Add frequency and presence penalty fields set to 1.2 to the set
of fields sent to server along with the user query. So that
the model is partly set to try avoid repeating text in its
response.

* SimpleChat:Add n_predict (equiv max_tokens) for llamacpp server

The /completions endpoint of examples/server doesnt take max_tokens,
instead it takes the internal n_predict, for now add the same on
the client side, maybe later add max_tokens to /completions endpoint
handling.

* SimpleChat: Note about trying to keep things simple yet flexible

2024-05-26 10:56:34 +10:00

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SimpleChat

by Humans for All.

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.

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.

NOTE: Given that the idea is for basic minimal testing, it doesnt bother with any model context length and culling of old messages from the chat by default. However by enabling the sliding window chat logic, a crude form of old messages culling can be achieved.

NOTE: It doesnt set any parameters other than temperature and max_tokens for now. However if someone wants they can update the js file or equivalent member in gMe as needed.

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 examples/server

bin/server -m path/model.gguf --path ../examples/server/public_simplechat [--port PORT]

running using python3's server module

first run examples/server

bin/server -m path/model.gguf

next run this web front end in examples/server/public_simplechat

cd ../examples/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

Select between chat and completion mode. By default it is set to chat mode.
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.
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.

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, for now. And 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.

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.

chatRequestOptions - maintains the list of options/fields to send along with chat 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.

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 chatRequestOptions.max_tokens 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.

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.

Concept of multiple chat sessions with different servers, as well as saving and restoring of those across browser usage sessions, can be woven around the SimpleChat/MultiChatUI class and its instances relatively easily, however given the current goal of keeping this simple, it has not been added, for now.

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.

read_json_early, is to experiment with reading json response data early on, if available, so that user can be shown generated data, as and when it is being generated, rather than at the end when full data is available.

the server flow doesnt seem to be sending back data early, atleast for request (inc options) that is currently sent.

if able to read json data early on in future, as and when ai model is generating data, then this helper needs to indirectly update the chat div with the recieved data, without waiting for the overall data to be available.

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.

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 examples/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.

Frequency and presence penalty fields are set to 1.2 in the set of fields sent to server along with the user query. So that the model is partly set to try avoid repeating text in its response.

A end-user can change these behaviour by editing gMe from browser's devel-tool/console.

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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