LibreChat/api/app/clients/tools/util/handleTools.js
Danny Avila 365c39c405
feat: Accurate Token Usage Tracking & Optional Balance (#1018)
* 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
2023-10-05 18:34:10 -04:00

264 lines
6.8 KiB
JavaScript

const { getUserPluginAuthValue } = require('../../../../server/services/PluginService');
const { OpenAIEmbeddings } = require('langchain/embeddings/openai');
const { ZapierToolKit } = require('langchain/agents');
const { SerpAPI, ZapierNLAWrapper } = require('langchain/tools');
const { ChatOpenAI } = require('langchain/chat_models/openai');
const { Calculator } = require('langchain/tools/calculator');
const { WebBrowser } = require('langchain/tools/webbrowser');
const {
availableTools,
CodeInterpreter,
AIPluginTool,
GoogleSearchAPI,
WolframAlphaAPI,
StructuredWolfram,
HttpRequestTool,
OpenAICreateImage,
StableDiffusionAPI,
StructuredSD,
AzureCognitiveSearch,
StructuredACS,
E2BTools,
CodeSherpa,
CodeSherpaTools,
CodeBrew,
} = require('../');
const { loadSpecs } = require('./loadSpecs');
const { loadToolSuite } = require('./loadToolSuite');
const getOpenAIKey = async (options, user) => {
let openAIApiKey = options.openAIApiKey ?? process.env.OPENAI_API_KEY;
openAIApiKey = openAIApiKey === 'user_provided' ? null : openAIApiKey;
return openAIApiKey || (await getUserPluginAuthValue(user, 'OPENAI_API_KEY'));
};
const validateTools = async (user, tools = []) => {
try {
const validToolsSet = new Set(tools);
const availableToolsToValidate = availableTools.filter((tool) =>
validToolsSet.has(tool.pluginKey),
);
const validateCredentials = async (authField, toolName) => {
const adminAuth = process.env[authField];
if (adminAuth && adminAuth.length > 0) {
return;
}
const userAuth = await getUserPluginAuthValue(user, authField);
if (userAuth && userAuth.length > 0) {
return;
}
validToolsSet.delete(toolName);
};
for (const tool of availableToolsToValidate) {
if (!tool.authConfig || tool.authConfig.length === 0) {
continue;
}
for (const auth of tool.authConfig) {
await validateCredentials(auth.authField, tool.pluginKey);
}
}
return Array.from(validToolsSet.values());
} catch (err) {
console.log('There was a problem validating tools', err);
throw new Error(err);
}
};
const loadToolWithAuth = async (user, authFields, ToolConstructor, options = {}) => {
return async function () {
let authValues = {};
for (const authField of authFields) {
let authValue = process.env[authField];
if (!authValue) {
authValue = await getUserPluginAuthValue(user, authField);
}
authValues[authField] = authValue;
}
return new ToolConstructor({ ...options, ...authValues });
};
};
const loadTools = async ({
user,
model,
functions = null,
returnMap = false,
tools = [],
options = {},
}) => {
const toolConstructors = {
calculator: Calculator,
codeinterpreter: CodeInterpreter,
google: GoogleSearchAPI,
wolfram: functions ? StructuredWolfram : WolframAlphaAPI,
'dall-e': OpenAICreateImage,
'stable-diffusion': functions ? StructuredSD : StableDiffusionAPI,
'azure-cognitive-search': functions ? StructuredACS : AzureCognitiveSearch,
CodeBrew: CodeBrew,
};
const openAIApiKey = await getOpenAIKey(options, user);
const customConstructors = {
e2b_code_interpreter: async () => {
if (!functions) {
return null;
}
return await loadToolSuite({
pluginKey: 'e2b_code_interpreter',
tools: E2BTools,
user,
options: {
model,
openAIApiKey,
...options,
},
});
},
codesherpa_tools: async () => {
if (!functions) {
return null;
}
return await loadToolSuite({
pluginKey: 'codesherpa_tools',
tools: CodeSherpaTools,
user,
options,
});
},
'web-browser': async () => {
// let openAIApiKey = options.openAIApiKey ?? process.env.OPENAI_API_KEY;
// openAIApiKey = openAIApiKey === 'user_provided' ? null : openAIApiKey;
// openAIApiKey = openAIApiKey || (await getUserPluginAuthValue(user, 'OPENAI_API_KEY'));
const browser = new WebBrowser({ model, embeddings: new OpenAIEmbeddings({ openAIApiKey }) });
browser.description_for_model = browser.description;
return browser;
},
serpapi: async () => {
let apiKey = process.env.SERPAPI_API_KEY;
if (!apiKey) {
apiKey = await getUserPluginAuthValue(user, 'SERPAPI_API_KEY');
}
return new SerpAPI(apiKey, {
location: 'Austin,Texas,United States',
hl: 'en',
gl: 'us',
});
},
zapier: async () => {
let apiKey = process.env.ZAPIER_NLA_API_KEY;
if (!apiKey) {
apiKey = await getUserPluginAuthValue(user, 'ZAPIER_NLA_API_KEY');
}
const zapier = new ZapierNLAWrapper({ apiKey });
return ZapierToolKit.fromZapierNLAWrapper(zapier);
},
plugins: async () => {
return [
new HttpRequestTool(),
await AIPluginTool.fromPluginUrl(
'https://www.klarna.com/.well-known/ai-plugin.json',
new ChatOpenAI({ openAIApiKey: options.openAIApiKey, temperature: 0 }),
),
];
},
};
const requestedTools = {};
if (functions) {
toolConstructors.codesherpa = CodeSherpa;
}
const toolOptions = {
serpapi: { location: 'Austin,Texas,United States', hl: 'en', gl: 'us' },
};
const toolAuthFields = {};
availableTools.forEach((tool) => {
if (customConstructors[tool.pluginKey]) {
return;
}
toolAuthFields[tool.pluginKey] = tool.authConfig.map((auth) => auth.authField);
});
const remainingTools = [];
for (const tool of tools) {
if (customConstructors[tool]) {
requestedTools[tool] = customConstructors[tool];
continue;
}
if (toolConstructors[tool]) {
const options = toolOptions[tool] || {};
const toolInstance = await loadToolWithAuth(
user,
toolAuthFields[tool],
toolConstructors[tool],
options,
);
requestedTools[tool] = toolInstance;
continue;
}
if (functions) {
remainingTools.push(tool);
}
}
let specs = null;
if (functions && remainingTools.length > 0) {
specs = await loadSpecs({
llm: model,
user,
message: options.message,
memory: options.memory,
signal: options.signal,
tools: remainingTools,
map: true,
verbose: false,
});
}
for (const tool of remainingTools) {
if (specs && specs[tool]) {
requestedTools[tool] = specs[tool];
}
}
if (returnMap) {
return requestedTools;
}
// load tools
let result = [];
for (const tool of tools) {
const validTool = requestedTools[tool];
const plugin = await validTool();
if (Array.isArray(plugin)) {
result = [...result, ...plugin];
} else if (plugin) {
result.push(plugin);
}
}
return result;
};
module.exports = {
validateTools,
loadTools,
};