LibreChat/api/app/clients/PluginsClient.js
Danny Avila 5d985746cb
🛠️ fix: Tool Filtering in PluginsClient (#3266)
* feat(plugins): implement tool filtering in PluginsClient

Add functionality to filter tools based on filteredTools and includedTools
arrays in the request's app locals. This allows for dynamic tool selection
on a per-request basis, enhancing the flexibility of the plugin system.

* test(plugins): add unit tests for tool filtering in PluginsClient

Introduce comprehensive test suite for the new tool filtering feature
in PluginsClient. Cover scenarios including filtering out tools,
including specific tools, prioritization of includedTools over
filteredTools, and behavior when no filters are provided.

* chore: Remove unused legacy Conversation component and update imports
2024-07-04 10:34:28 -04:00

528 lines
18 KiB
JavaScript

const OpenAIClient = require('./OpenAIClient');
const { CallbackManager } = require('langchain/callbacks');
const { BufferMemory, ChatMessageHistory } = require('langchain/memory');
const { initializeCustomAgent, initializeFunctionsAgent } = require('./agents');
const { addImages, buildErrorInput, buildPromptPrefix } = require('./output_parsers');
const { processFileURL } = require('~/server/services/Files/process');
const { EModelEndpoint } = require('librechat-data-provider');
const { formatLangChainMessages } = require('./prompts');
const checkBalance = require('~/models/checkBalance');
const { SelfReflectionTool } = require('./tools');
const { isEnabled } = require('~/server/utils');
const { extractBaseURL } = require('~/utils');
const { loadTools } = require('./tools/util');
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 {
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),
});
this.tools = 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,
},
});
if (this.tools.length > 0 && !this.functionsAgent) {
this.tools.push(new SelfReflectionTool({ message, isGpt3: false }));
} else if (this.tools.length === 0) {
return;
}
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;
this.executor = await initializer({
model,
signal,
pastMessages,
tools: this.tools,
verbose: this.options.debug,
returnIntermediateSteps: true,
customName: this.options.chatGptLabel,
currentDateString: this.currentDateString,
customInstructions: this.options.promptPrefix,
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;
}
}
}
}
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);
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',
name: 'instructions',
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;