mirror of
https://github.com/danny-avila/LibreChat.git
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* 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
132 lines
3.3 KiB
JavaScript
132 lines
3.3 KiB
JavaScript
const fs = require('fs');
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const path = require('path');
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const { z } = require('zod');
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const { createOpenAPIPlugin } = require('../dynamic/OpenAPIPlugin');
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// The minimum Manifest definition
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const ManifestDefinition = z.object({
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schema_version: z.string().optional(),
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name_for_human: z.string(),
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name_for_model: z.string(),
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description_for_human: z.string(),
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description_for_model: z.string(),
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auth: z.object({}).optional(),
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api: z.object({
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// Spec URL or can be the filename of the OpenAPI spec yaml file,
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// located in api\app\clients\tools\.well-known\openapi
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url: z.string(),
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type: z.string().optional(),
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is_user_authenticated: z.boolean().nullable().optional(),
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has_user_authentication: z.boolean().nullable().optional(),
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}),
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// use to override any params that the LLM will consistently get wrong
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params: z.object({}).optional(),
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logo_url: z.string().optional(),
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contact_email: z.string().optional(),
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legal_info_url: z.string().optional(),
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});
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function validateJson(json, verbose = true) {
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try {
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return ManifestDefinition.parse(json);
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} catch (error) {
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if (verbose) {
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console.debug('validateJson error', error);
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}
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return false;
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}
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}
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// omit the LLM to return the well known jsons as objects
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async function loadSpecs({
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llm,
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user,
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message,
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tools = [],
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map = false,
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memory,
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signal,
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verbose = false,
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}) {
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const directoryPath = path.join(__dirname, '..', '.well-known');
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let files = [];
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for (let i = 0; i < tools.length; i++) {
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const filePath = path.join(directoryPath, tools[i] + '.json');
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try {
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// If the access Promise is resolved, it means that the file exists
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// Then we can add it to the files array
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await fs.promises.access(filePath, fs.constants.F_OK);
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files.push(tools[i] + '.json');
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} catch (err) {
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console.error(`File ${tools[i] + '.json'} does not exist`);
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}
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}
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if (files.length === 0) {
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files = (await fs.promises.readdir(directoryPath)).filter(
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(file) => path.extname(file) === '.json',
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);
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}
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const validJsons = [];
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const constructorMap = {};
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if (verbose) {
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console.debug('files', files);
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}
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for (const file of files) {
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if (path.extname(file) === '.json') {
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const filePath = path.join(directoryPath, file);
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const fileContent = await fs.promises.readFile(filePath, 'utf8');
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const json = JSON.parse(fileContent);
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if (!validateJson(json)) {
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verbose && console.debug('Invalid json', json);
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continue;
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}
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if (llm && map) {
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constructorMap[json.name_for_model] = async () =>
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await createOpenAPIPlugin({
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data: json,
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llm,
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message,
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memory,
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signal,
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user,
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verbose,
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});
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continue;
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}
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if (llm) {
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validJsons.push(createOpenAPIPlugin({ data: json, llm, verbose }));
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continue;
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}
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validJsons.push(json);
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}
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}
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if (map) {
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return constructorMap;
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}
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const plugins = (await Promise.all(validJsons)).filter((plugin) => plugin);
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// if (verbose) {
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// console.debug('plugins', plugins);
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// console.debug(plugins[0].name);
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// }
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return plugins;
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}
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module.exports = {
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loadSpecs,
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validateJson,
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ManifestDefinition,
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};
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