LibreChat/api/app/clients/PluginsClient.js
Danny Avila 1a815f5e19
🎉 feat: Code Interpreter API and Agents Release (#4860)
* feat: Code Interpreter API & File Search Agent Uploads

chore: add back code files

wip: first pass, abstract key dialog

refactor: influence checkbox on key changes

refactor: update localization keys for 'execute code' to 'run code'

wip: run code button

refactor: add throwError parameter to loadAuthValues and getUserPluginAuthValue functions

feat: first pass, API tool calling

fix: handle missing toolId in callTool function and return 404 for non-existent tools

feat: show code outputs

fix: improve error handling in callTool function and log errors

fix: handle potential null value for filepath in attachment destructuring

fix: normalize language before rendering and prevent null return

fix: add loading indicator in RunCode component while executing code

feat: add support for conditional code execution in Markdown components

feat: attachments

refactor: remove bash

fix: pass abort signal to graph/run

refactor: debounce and rate limit tool call

refactor: increase debounce delay for execute function

feat: set code output attachments

feat: image attachments

refactor: apply message context

refactor: pass `partIndex`

feat: toolCall schema/model/methods

feat: block indexing

feat: get tool calls

chore: imports

chore: typing

chore: condense type imports

feat: get tool calls

fix: block indexing

chore: typing

refactor: update tool calls mapping to support multiple results

fix: add unique key to nav link for rendering

wip: first pass, tool call results

refactor: update query cache from successful tool call mutation

style: improve result switcher styling

chore: note on using \`.toObject()\`

feat: add agent_id field to conversation schema

chore: typing

refactor: rename agentMap to agentsMap for consistency

feat: Agent Name as chat input placeholder

chore: bump agents

📦 chore: update @langchain dependencies to latest versions to match agents package

📦 chore: update @librechat/agents dependency to version 1.8.0

fix: Aborting agent stream removes sender; fix(bedrock): completion removes preset name label

refactor: remove direct file parameter to use req.file, add `processAgentFileUpload` for image uploads

feat: upload menu

feat: prime message_file resources

feat: implement conversation access validation in chat route

refactor: remove file parameter from processFileUpload and use req.file instead

feat: add savedMessageIds set to track saved message IDs in BaseClient, to prevent unnecessary double-write to db

feat: prevent duplicate message saves by checking savedMessageIds in AgentController

refactor: skip legacy RAG API handling for agents

feat: add files field to convoSchema

refactor: update request type annotations from Express.Request to ServerRequest in file processing functions

feat: track conversation files

fix: resendFiles, addPreviousAttachments handling

feat: add ID validation for session_id and file_id in download route

feat: entity_id for code file uploads/downloads

fix: code file edge cases

feat: delete related tool calls

feat: add stream rate handling for LLM configuration

feat: enhance system content with attached file information

fix: improve error logging in resource priming function

* WIP: PoC, sequential agents

WIP: PoC Sequential Agents, first pass content data + bump agents package

fix: package-lock

WIP: PoC, o1 support, refactor bufferString

feat: convertJsonSchemaToZod

fix: form issues and schema defining erroneous model

fix: max length issue on agent form instructions, limit conversation messages to sequential agents

feat: add abort signal support to createRun function and AgentClient

feat: PoC, hide prior sequential agent steps

fix: update parameter naming from config to metadata in event handlers for clarity, add model to usage data

refactor: use only last contentData, track model for usage data

chore: bump agents package

fix: content parts issue

refactor: filter contentParts to include tool calls and relevant indices

feat: show function calls

refactor: filter context messages to exclude tool calls when no tools are available to the agent

fix: ensure tool call content is not undefined in formatMessages

feat: add agent_id field to conversationPreset schema

feat: hide sequential agents

feat: increase upload toast duration to 10 seconds

* refactor: tool context handling & update Code API Key Dialog

feat: toolContextMap

chore: skipSpecs -> useSpecs

ci: fix handleTools tests

feat: API Key Dialog

* feat: Agent Permissions Admin Controls

feat: replace label with button for prompt permission toggle

feat: update agent permissions

feat: enable experimental agents and streamline capability configuration

feat: implement access control for agents and enhance endpoint menu items

feat: add welcome message for agent selection in localization

feat: add agents permission to access control and update version to 0.7.57

* fix: update types in useAssistantListMap and useMentions hooks for better null handling

* feat: mention agents

* fix: agent tool resource race conditions when deleting agent tool resource files

* feat: add error handling for code execution with user feedback

* refactor: rename AdminControls to AdminSettings for clarity

* style: add gap to button in AdminSettings for improved layout

* refactor: separate agent query hooks and check access to enable fetching

* fix: remove unused provider from agent initialization options, creates issue with custom endpoints

* refactor: remove redundant/deprecated modelOptions from AgentClient processes

* chore: update @librechat/agents to version 1.8.5 in package.json and package-lock.json

* fix: minor styling issues + agent panel uniformity

* fix: agent edge cases when set endpoint is no longer defined

* refactor: remove unused cleanup function call from AppService

* fix: update link in ApiKeyDialog to point to pricing page

* fix: improve type handling and layout calculations in SidePanel component

* fix: add missing localization string for agent selection in SidePanel

* chore: form styling and localizations for upload filesearch/code interpreter

* fix: model selection placeholder logic in AgentConfig component

* style: agent capabilities

* fix: add localization for provider selection and improve dropdown styling in ModelPanel

* refactor: use gpt-4o-mini > gpt-3.5-turbo

* fix: agents configuration for loadDefaultInterface and update related tests

* feat: DALLE Agents support
2024-12-04 15:48:13 -05:00

552 lines
18 KiB
JavaScript

const OpenAIClient = require('./OpenAIClient');
const { CacheKeys, Time } = require('librechat-data-provider');
const { CallbackManager } = require('@langchain/core/callbacks/manager');
const { BufferMemory, ChatMessageHistory } = require('langchain/memory');
const { addImages, buildErrorInput, buildPromptPrefix } = require('./output_parsers');
const { initializeCustomAgent, initializeFunctionsAgent } = require('./agents');
const { processFileURL } = require('~/server/services/Files/process');
const { EModelEndpoint } = require('librechat-data-provider');
const { formatLangChainMessages } = require('./prompts');
const checkBalance = require('~/models/checkBalance');
const { isEnabled } = require('~/server/utils');
const { extractBaseURL } = require('~/utils');
const { loadTools } = require('./tools/util');
const { getLogStores } = require('~/cache');
const { logger } = require('~/config');
class PluginsClient extends OpenAIClient {
constructor(apiKey, options = {}) {
super(apiKey, options);
this.sender = options.sender ?? 'Assistant';
this.tools = [];
this.actions = [];
this.setOptions(options);
this.openAIApiKey = this.apiKey;
this.executor = null;
}
setOptions(options) {
this.agentOptions = { ...options.agentOptions };
this.functionsAgent = this.agentOptions?.agent === 'functions';
this.agentIsGpt3 = this.agentOptions?.model?.includes('gpt-3');
super.setOptions(options);
this.isGpt3 = this.modelOptions?.model?.includes('gpt-3');
if (this.options.reverseProxyUrl) {
this.langchainProxy = extractBaseURL(this.options.reverseProxyUrl);
}
}
getSaveOptions() {
return {
artifacts: this.options.artifacts,
chatGptLabel: this.options.chatGptLabel,
promptPrefix: this.options.promptPrefix,
tools: this.options.tools,
...this.modelOptions,
agentOptions: this.agentOptions,
iconURL: this.options.iconURL,
greeting: this.options.greeting,
spec: this.options.spec,
};
}
saveLatestAction(action) {
this.actions.push(action);
}
getFunctionModelName(input) {
if (/-(?!0314)\d{4}/.test(input)) {
return input;
} else if (input.includes('gpt-3.5-turbo')) {
return 'gpt-3.5-turbo';
} else if (input.includes('gpt-4')) {
return 'gpt-4';
} else {
return 'gpt-3.5-turbo';
}
}
getBuildMessagesOptions(opts) {
return {
isChatCompletion: true,
promptPrefix: opts.promptPrefix,
abortController: opts.abortController,
};
}
async initialize({ user, message, onAgentAction, onChainEnd, signal }) {
const modelOptions = {
modelName: this.agentOptions.model,
temperature: this.agentOptions.temperature,
};
const model = this.initializeLLM({
...modelOptions,
context: 'plugins',
initialMessageCount: this.currentMessages.length + 1,
});
logger.debug(
`[PluginsClient] Agent Model: ${model.modelName} | Temp: ${model.temperature} | Functions: ${this.functionsAgent}`,
);
// Map Messages to Langchain format
const pastMessages = formatLangChainMessages(this.currentMessages.slice(0, -1), {
userName: this.options?.name,
});
logger.debug('[PluginsClient] pastMessages: ' + pastMessages.length);
// TODO: use readOnly memory, TokenBufferMemory? (both unavailable in LangChainJS)
const memory = new BufferMemory({
llm: model,
chatHistory: new ChatMessageHistory(pastMessages),
});
const { loadedTools } = await loadTools({
user,
model,
tools: this.options.tools,
functions: this.functionsAgent,
options: {
memory,
signal: this.abortController.signal,
openAIApiKey: this.openAIApiKey,
conversationId: this.conversationId,
fileStrategy: this.options.req.app.locals.fileStrategy,
processFileURL,
message,
},
useSpecs: true,
});
if (loadedTools.length === 0) {
return;
}
this.tools = loadedTools;
logger.debug('[PluginsClient] Requested Tools', this.options.tools);
logger.debug(
'[PluginsClient] Loaded Tools',
this.tools.map((tool) => tool.name),
);
const handleAction = (action, runId, callback = null) => {
this.saveLatestAction(action);
logger.debug('[PluginsClient] Latest Agent Action ', this.actions[this.actions.length - 1]);
if (typeof callback === 'function') {
callback(action, runId);
}
};
// initialize agent
const initializer = this.functionsAgent ? initializeFunctionsAgent : initializeCustomAgent;
let customInstructions = (this.options.promptPrefix ?? '').trim();
if (typeof this.options.artifactsPrompt === 'string' && this.options.artifactsPrompt) {
customInstructions = `${customInstructions ?? ''}\n${this.options.artifactsPrompt}`.trim();
}
this.executor = await initializer({
model,
signal,
pastMessages,
tools: this.tools,
customInstructions,
verbose: this.options.debug,
returnIntermediateSteps: true,
customName: this.options.chatGptLabel,
currentDateString: this.currentDateString,
callbackManager: CallbackManager.fromHandlers({
async handleAgentAction(action, runId) {
handleAction(action, runId, onAgentAction);
},
async handleChainEnd(action) {
if (typeof onChainEnd === 'function') {
onChainEnd(action);
}
},
}),
});
logger.debug('[PluginsClient] Loaded agent.');
}
async executorCall(message, { signal, stream, onToolStart, onToolEnd }) {
let errorMessage = '';
const maxAttempts = 1;
for (let attempts = 1; attempts <= maxAttempts; attempts++) {
const errorInput = buildErrorInput({
message,
errorMessage,
actions: this.actions,
functionsAgent: this.functionsAgent,
});
const input = attempts > 1 ? errorInput : message;
logger.debug(`[PluginsClient] Attempt ${attempts} of ${maxAttempts}`);
if (errorMessage.length > 0) {
logger.debug('[PluginsClient] Caught error, input: ' + JSON.stringify(input));
}
try {
this.result = await this.executor.call({ input, signal }, [
{
async handleToolStart(...args) {
await onToolStart(...args);
},
async handleToolEnd(...args) {
await onToolEnd(...args);
},
async handleLLMEnd(output) {
const { generations } = output;
const { text } = generations[0][0];
if (text && typeof stream === 'function') {
await stream(text);
}
},
},
]);
break; // Exit the loop if the function call is successful
} catch (err) {
logger.error('[PluginsClient] executorCall error:', err);
if (attempts === maxAttempts) {
const { run } = this.runManager.getRunByConversationId(this.conversationId);
const defaultOutput = `Encountered an error while attempting to respond: ${err.message}`;
this.result.output = run && run.error ? run.error : defaultOutput;
this.result.errorMessage = run && run.error ? run.error : err.message;
this.result.intermediateSteps = this.actions;
break;
}
}
}
}
/**
*
* @param {TMessage} responseMessage
* @param {Partial<TMessage>} saveOptions
* @param {string} user
* @returns
*/
async handleResponseMessage(responseMessage, saveOptions, user) {
const { output, errorMessage, ...result } = this.result;
logger.debug('[PluginsClient][handleResponseMessage] Output:', {
output,
errorMessage,
...result,
});
const { error } = responseMessage;
if (!error) {
responseMessage.tokenCount = this.getTokenCountForResponse(responseMessage);
responseMessage.completionTokens = this.getTokenCount(responseMessage.text);
}
// Record usage only when completion is skipped as it is already recorded in the agent phase.
if (!this.agentOptions.skipCompletion && !error) {
await this.recordTokenUsage(responseMessage);
}
this.responsePromise = this.saveMessageToDatabase(responseMessage, saveOptions, user);
const messageCache = getLogStores(CacheKeys.MESSAGES);
messageCache.set(
responseMessage.messageId,
{
text: responseMessage.text,
complete: true,
},
Time.FIVE_MINUTES,
);
delete responseMessage.tokenCount;
return { ...responseMessage, ...result };
}
async sendMessage(message, opts = {}) {
/** @type {{ filteredTools: string[], includedTools: string[] }} */
const { filteredTools = [], includedTools = [] } = this.options.req.app.locals;
if (includedTools.length > 0) {
const tools = this.options.tools.filter((plugin) => includedTools.includes(plugin));
this.options.tools = tools;
} else {
const tools = this.options.tools.filter((plugin) => !filteredTools.includes(plugin));
this.options.tools = tools;
}
// If a message is edited, no tools can be used.
const completionMode = this.options.tools.length === 0 || opts.isEdited;
if (completionMode) {
this.setOptions(opts);
return super.sendMessage(message, opts);
}
logger.debug('[PluginsClient] sendMessage', { userMessageText: message, opts });
const {
user,
isEdited,
conversationId,
responseMessageId,
saveOptions,
userMessage,
onAgentAction,
onChainEnd,
onToolStart,
onToolEnd,
} = await this.handleStartMethods(message, opts);
if (opts.progressCallback) {
opts.onProgress = opts.progressCallback.call(null, {
...(opts.progressOptions ?? {}),
parentMessageId: userMessage.messageId,
messageId: responseMessageId,
});
}
this.currentMessages.push(userMessage);
let {
prompt: payload,
tokenCountMap,
promptTokens,
} = await this.buildMessages(
this.currentMessages,
userMessage.messageId,
this.getBuildMessagesOptions({
promptPrefix: null,
abortController: this.abortController,
}),
);
if (tokenCountMap) {
logger.debug('[PluginsClient] tokenCountMap', { tokenCountMap });
if (tokenCountMap[userMessage.messageId]) {
userMessage.tokenCount = tokenCountMap[userMessage.messageId];
logger.debug('[PluginsClient] userMessage.tokenCount', userMessage.tokenCount);
}
this.handleTokenCountMap(tokenCountMap);
}
this.result = {};
if (payload) {
this.currentMessages = payload;
}
if (!this.skipSaveUserMessage) {
this.userMessagePromise = this.saveMessageToDatabase(userMessage, saveOptions, user);
if (typeof opts?.getReqData === 'function') {
opts.getReqData({
userMessagePromise: this.userMessagePromise,
});
}
}
if (isEnabled(process.env.CHECK_BALANCE)) {
await checkBalance({
req: this.options.req,
res: this.options.res,
txData: {
user: this.user,
tokenType: 'prompt',
amount: promptTokens,
debug: this.options.debug,
model: this.modelOptions.model,
endpoint: EModelEndpoint.openAI,
},
});
}
const responseMessage = {
endpoint: EModelEndpoint.gptPlugins,
iconURL: this.options.iconURL,
messageId: responseMessageId,
conversationId,
parentMessageId: userMessage.messageId,
isCreatedByUser: false,
isEdited,
model: this.modelOptions.model,
sender: this.sender,
promptTokens,
};
await this.initialize({
user,
message,
onAgentAction,
onChainEnd,
signal: this.abortController.signal,
onProgress: opts.onProgress,
});
// const stream = async (text) => {
// await this.generateTextStream.call(this, text, opts.onProgress, { delay: 1 });
// };
await this.executorCall(message, {
signal: this.abortController.signal,
// stream,
onToolStart,
onToolEnd,
});
// If message was aborted mid-generation
if (this.result?.errorMessage?.length > 0 && this.result?.errorMessage?.includes('cancel')) {
responseMessage.text = 'Cancelled.';
return await this.handleResponseMessage(responseMessage, saveOptions, user);
}
// If error occurred during generation (likely token_balance)
if (this.result?.errorMessage?.length > 0) {
responseMessage.error = true;
responseMessage.text = this.result.output;
return await this.handleResponseMessage(responseMessage, saveOptions, user);
}
if (this.agentOptions.skipCompletion && this.result.output && this.functionsAgent) {
const partialText = opts.getPartialText();
const trimmedPartial = opts.getPartialText().replaceAll(':::plugin:::\n', '');
responseMessage.text =
trimmedPartial.length === 0 ? `${partialText}${this.result.output}` : partialText;
addImages(this.result.intermediateSteps, responseMessage);
await this.generateTextStream(this.result.output, opts.onProgress, { delay: 5 });
return await this.handleResponseMessage(responseMessage, saveOptions, user);
}
if (this.agentOptions.skipCompletion && this.result.output) {
responseMessage.text = this.result.output;
addImages(this.result.intermediateSteps, responseMessage);
await this.generateTextStream(this.result.output, opts.onProgress, { delay: 5 });
return await this.handleResponseMessage(responseMessage, saveOptions, user);
}
logger.debug('[PluginsClient] Completion phase: this.result', this.result);
const promptPrefix = buildPromptPrefix({
result: this.result,
message,
functionsAgent: this.functionsAgent,
});
logger.debug('[PluginsClient]', { promptPrefix });
payload = await this.buildCompletionPrompt({
messages: this.currentMessages,
promptPrefix,
});
logger.debug('[PluginsClient] buildCompletionPrompt Payload', payload);
responseMessage.text = await this.sendCompletion(payload, opts);
return await this.handleResponseMessage(responseMessage, saveOptions, user);
}
async buildCompletionPrompt({ messages, promptPrefix: _promptPrefix }) {
logger.debug('[PluginsClient] buildCompletionPrompt messages', messages);
const orderedMessages = messages;
let promptPrefix = _promptPrefix.trim();
// If the prompt prefix doesn't end with the end token, add it.
if (!promptPrefix.endsWith(`${this.endToken}`)) {
promptPrefix = `${promptPrefix.trim()}${this.endToken}\n\n`;
}
promptPrefix = `${this.startToken}Instructions:\n${promptPrefix}`;
const promptSuffix = `${this.startToken}${this.chatGptLabel ?? 'Assistant'}:\n`;
const instructionsPayload = {
role: 'system',
content: promptPrefix,
};
const messagePayload = {
role: 'system',
content: promptSuffix,
};
if (this.isGpt3) {
instructionsPayload.role = 'user';
messagePayload.role = 'user';
instructionsPayload.content += `\n${promptSuffix}`;
}
// testing if this works with browser endpoint
if (!this.isGpt3 && this.options.reverseProxyUrl) {
instructionsPayload.role = 'user';
}
let currentTokenCount =
this.getTokenCountForMessage(instructionsPayload) +
this.getTokenCountForMessage(messagePayload);
let promptBody = '';
const maxTokenCount = this.maxPromptTokens;
// Iterate backwards through the messages, adding them to the prompt until we reach the max token count.
// Do this within a recursive async function so that it doesn't block the event loop for too long.
const buildPromptBody = async () => {
if (currentTokenCount < maxTokenCount && orderedMessages.length > 0) {
const message = orderedMessages.pop();
const isCreatedByUser = message.isCreatedByUser || message.role?.toLowerCase() === 'user';
const roleLabel = isCreatedByUser ? this.userLabel : this.chatGptLabel;
let messageString = `${this.startToken}${roleLabel}:\n${
message.text ?? message.content ?? ''
}${this.endToken}\n`;
let newPromptBody = `${messageString}${promptBody}`;
const tokenCountForMessage = this.getTokenCount(messageString);
const newTokenCount = currentTokenCount + tokenCountForMessage;
if (newTokenCount > maxTokenCount) {
if (promptBody) {
// This message would put us over the token limit, so don't add it.
return false;
}
// This is the first message, so we can't add it. Just throw an error.
throw new Error(
`Prompt is too long. Max token count is ${maxTokenCount}, but prompt is ${newTokenCount} tokens long.`,
);
}
promptBody = newPromptBody;
currentTokenCount = newTokenCount;
// wait for next tick to avoid blocking the event loop
await new Promise((resolve) => setTimeout(resolve, 0));
return buildPromptBody();
}
return true;
};
await buildPromptBody();
const prompt = promptBody;
messagePayload.content = prompt;
// Add 2 tokens for metadata after all messages have been counted.
currentTokenCount += 2;
if (this.isGpt3 && messagePayload.content.length > 0) {
const context = 'Chat History:\n';
messagePayload.content = `${context}${prompt}`;
currentTokenCount += this.getTokenCount(context);
}
// Use up to `this.maxContextTokens` tokens (prompt + response), but try to leave `this.maxTokens` tokens for the response.
this.modelOptions.max_tokens = Math.min(
this.maxContextTokens - currentTokenCount,
this.maxResponseTokens,
);
if (this.isGpt3) {
messagePayload.content += promptSuffix;
return [instructionsPayload, messagePayload];
}
const result = [messagePayload, instructionsPayload];
if (this.functionsAgent && !this.isGpt3) {
result[1].content = `${result[1].content}\n${this.startToken}${this.chatGptLabel}:\nSure thing! Here is the output you requested:\n`;
}
return result.filter((message) => message.content.length > 0);
}
}
module.exports = PluginsClient;