mirror of
https://github.com/danny-avila/LibreChat.git
synced 2025-12-18 01:10:14 +01:00
* refactor(Chains/llms): allow passing callbacks * refactor(BaseClient): accurately count completion tokens as generation only * refactor(OpenAIClient): remove unused getTokenCountForResponse, pass streaming var and callbacks in initializeLLM * wip: summary prompt tokens * refactor(summarizeMessages): new cut-off strategy that generates a better summary by adding context from beginning, truncating the middle, and providing the end wip: draft out relevant providers and variables for token tracing * refactor(createLLM): make streaming prop false by default * chore: remove use of getTokenCountForResponse * refactor(agents): use BufferMemory as ConversationSummaryBufferMemory token usage not easy to trace * chore: remove passing of streaming prop, also console log useful vars for tracing * feat: formatFromLangChain helper function to count tokens for ChatModelStart * refactor(initializeLLM): add role for LLM tracing * chore(formatFromLangChain): update JSDoc * feat(formatMessages): formats langChain messages into OpenAI payload format * chore: install openai-chat-tokens * refactor(formatMessage): optimize conditional langChain logic fix(formatFromLangChain): fix destructuring * feat: accurate prompt tokens for ChatModelStart before generation * refactor(handleChatModelStart): move to callbacks dir, use factory function * refactor(initializeLLM): rename 'role' to 'context' * feat(Balance/Transaction): new schema/models for tracking token spend refactor(Key): factor out model export to separate file * refactor(initializeClient): add req,res objects to client options * feat: add-balance script to add to an existing users' token balance refactor(Transaction): use multiplier map/function, return balance update * refactor(Tx): update enum for tokenType, return 1 for multiplier if no map match * refactor(Tx): add fair fallback value multiplier incase the config result is undefined * refactor(Balance): rename 'tokens' to 'tokenCredits' * feat: balance check, add tx.js for new tx-related methods and tests * chore(summaryPrompts): update prompt token count * refactor(callbacks): pass req, res wip: check balance * refactor(Tx): make convoId a String type, fix(calculateTokenValue) * refactor(BaseClient): add conversationId as client prop when assigned * feat(RunManager): track LLM runs with manager, track token spend from LLM, refactor(OpenAIClient): use RunManager to create callbacks, pass user prop to langchain api calls * feat(spendTokens): helper to spend prompt/completion tokens * feat(checkBalance): add helper to check, log, deny request if balance doesn't have enough funds refactor(Balance): static check method to return object instead of boolean now wip(OpenAIClient): implement use of checkBalance * refactor(initializeLLM): add token buffer to assure summary isn't generated when subsequent payload is too large refactor(OpenAIClient): add checkBalance refactor(createStartHandler): add checkBalance * chore: remove prompt and completion token logging from route handler * chore(spendTokens): add JSDoc * feat(logTokenCost): record transactions for basic api calls * chore(ask/edit): invoke getResponseSender only once per API call * refactor(ask/edit): pass promptTokens to getIds and include in abort data * refactor(getIds -> getReqData): rename function * refactor(Tx): increase value if incomplete message * feat: record tokenUsage when message is aborted * refactor: subtract tokens when payload includes function_call * refactor: add namespace for token_balance * fix(spendTokens): only execute if corresponding token type amounts are defined * refactor(checkBalance): throws Error if not enough token credits * refactor(runTitleChain): pass and use signal, spread object props in create helpers, and use 'call' instead of 'run' * fix(abortMiddleware): circular dependency, and default to empty string for completionTokens * fix: properly cancel title requests when there isn't enough tokens to generate * feat(predictNewSummary): custom chain for summaries to allow signal passing refactor(summaryBuffer): use new custom chain * feat(RunManager): add getRunByConversationId method, refactor: remove run and throw llm error on handleLLMError * refactor(createStartHandler): if summary, add error details to runs * fix(OpenAIClient): support aborting from summarization & showing error to user refactor(summarizeMessages): remove unnecessary operations counting summaryPromptTokens and note for alternative, pass signal to summaryBuffer * refactor(logTokenCost -> recordTokenUsage): rename * refactor(checkBalance): include promptTokens in errorMessage * refactor(checkBalance/spendTokens): move to models dir * fix(createLanguageChain): correctly pass config * refactor(initializeLLM/title): add tokenBuffer of 150 for balance check * refactor(openAPIPlugin): pass signal and memory, filter functions by the one being called * refactor(createStartHandler): add error to run if context is plugins as well * refactor(RunManager/handleLLMError): throw error immediately if plugins, don't remove run * refactor(PluginsClient): pass memory and signal to tools, cleanup error handling logic * chore: use absolute equality for addTitle condition * refactor(checkBalance): move checkBalance to execute after userMessage and tokenCounts are saved, also make conditional * style: icon changes to match official * fix(BaseClient): getTokenCountForResponse -> getTokenCount * fix(formatLangChainMessages): add kwargs as fallback prop from lc_kwargs, update JSDoc * refactor(Tx.create): does not update balance if CHECK_BALANCE is not enabled * fix(e2e/cleanUp): cleanup new collections, import all model methods from index * fix(config/add-balance): add uncaughtException listener * fix: circular dependency * refactor(initializeLLM/checkBalance): append new generations to errorMessage if cost exceeds balance * fix(handleResponseMessage): only record token usage in this method if not error and completion is not skipped * fix(createStartHandler): correct condition for generations * chore: bump postcss due to moderate severity vulnerability * chore: bump zod due to low severity vulnerability * chore: bump openai & data-provider version * feat(types): OpenAI Message types * chore: update bun lockfile * refactor(CodeBlock): add error block formatting * refactor(utils/Plugin): factor out formatJSON and cn to separate files (json.ts and cn.ts), add extractJSON * chore(logViolation): delete user_id after error is logged * refactor(getMessageError -> Error): change to React.FC, add token_balance handling, use extractJSON to determine JSON instead of regex * fix(DALL-E): use latest openai SDK * chore: reorganize imports, fix type issue * feat(server): add balance route * fix(api/models): add auth * feat(data-provider): /api/balance query * feat: show balance if checking is enabled, refetch on final message or error * chore: update docs, .env.example with token_usage info, add balance script command * fix(Balance): fallback to empty obj for balance query * style: slight adjustment of balance element * docs(token_usage): add PR notes
106 lines
3.1 KiB
TypeScript
106 lines
3.1 KiB
TypeScript
import React from 'react';
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import { Plugin, GPTIcon, AnthropicIcon, AzureMinimalIcon } from '~/components/svg';
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import { useAuthContext } from '~/hooks';
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import { cn } from '~/utils';
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import { IconProps } from '~/common';
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const Icon: React.FC<IconProps> = (props) => {
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const { size = 30, isCreatedByUser, button, model = true, endpoint, error, jailbreak } = props;
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const { user } = useAuthContext();
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if (isCreatedByUser) {
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const username = user?.name || 'User';
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return (
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<div
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title={username}
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style={{
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width: size,
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height: size,
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}}
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className={`relative flex items-center justify-center ${props.className ?? ''}`}
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>
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<img
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className="rounded-sm"
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src={
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user?.avatar ||
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`https://api.dicebear.com/6.x/initials/svg?seed=${username}&fontFamily=Verdana&fontSize=36`
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}
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alt="avatar"
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/>
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</div>
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);
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} else {
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const endpointIcons = {
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azureOpenAI: {
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icon: <AzureMinimalIcon size={size * 0.5555555555555556} />,
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bg: 'linear-gradient(0.375turn, #61bde2, #4389d0)',
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name: 'ChatGPT',
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},
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openAI: {
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icon: <GPTIcon size={size * 0.5555555555555556} />,
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bg:
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typeof model === 'string' && model.toLowerCase().includes('gpt-4')
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? '#AB68FF'
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: '#19C37D',
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name: 'ChatGPT',
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},
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gptPlugins: {
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icon: <Plugin size={size * 0.7} />,
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bg: `rgba(69, 89, 164, ${button ? 0.75 : 1})`,
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name: 'Plugins',
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},
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google: { icon: <img src="/assets/google-palm.svg" alt="Palm Icon" />, name: 'PaLM2' },
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anthropic: {
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icon: <AnthropicIcon size={size * 0.5555555555555556} />,
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bg: '#d09a74',
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name: 'Claude',
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},
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bingAI: {
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icon: jailbreak ? (
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<img src="/assets/bingai-jb.png" alt="Bing Icon" />
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) : (
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<img src="/assets/bingai.png" alt="Sydney Icon" />
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),
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name: jailbreak ? 'Sydney' : 'BingAI',
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},
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chatGPTBrowser: {
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icon: <GPTIcon size={size * 0.5555555555555556} />,
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bg:
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typeof model === 'string' && model.toLowerCase().includes('gpt-4')
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? '#AB68FF'
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: `rgba(0, 163, 255, ${button ? 0.75 : 1})`,
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name: 'ChatGPT',
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},
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null: { icon: <GPTIcon size={size * 0.7} />, bg: 'grey', name: 'N/A' },
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default: { icon: <GPTIcon size={size * 0.7} />, bg: 'grey', name: 'UNKNOWN' },
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};
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const { icon, bg, name } = endpointIcons[endpoint ?? 'default'];
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return (
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<div
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title={name}
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style={{
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background: bg || 'transparent',
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width: size,
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height: size,
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}}
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className={cn(
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'relative flex items-center justify-center rounded-sm text-white ',
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props.className || '',
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)}
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>
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{icon}
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{error && (
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<span className="absolute right-0 top-[20px] -mr-2 flex h-4 w-4 items-center justify-center rounded-full border border-white bg-red-500 text-[10px] text-white">
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!
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</span>
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)}
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</div>
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);
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}
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};
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export default Icon;
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