mirror of
https://github.com/danny-avila/LibreChat.git
synced 2025-09-22 08:12:00 +02:00

* feat(PluginsClient.js): add conversationId to options object in the constructor feat(PluginsClient.js): add support for Code Interpreter plugin feat(PluginsClient.js): add support for Code Interpreter plugin in the availableTools manifest feat(CodeInterpreter.js): add CodeInterpreterTools module feat(CodeInterpreter.js): add RunCommand class feat(CodeInterpreter.js): add ReadFile class feat(CodeInterpreter.js): add WriteFile class feat(handleTools.js): add support for loading Code Interpreter plugin * chore(api): update langchain dependency to version 0.0.123 * fix(CodeInterpreter.js): add support for extracting environment from code fix(WriteFile.js): add support for extracting environment from data fix(extractionChain.js): add utility functions for creating extraction chain from Zod schema fix(handleTools.js): refactor getOpenAIKey function to handle user-provided API key fix(handleTools.js): pass model and openAIApiKey to CodeInterpreter constructor * fix(tools): rename CodeInterpreterTools to E2BTools fix(tools): rename code_interpreter pluginKey to e2b_code_interpreter * chore(PluginsClient.js): comment out unused import and function findMessageContent feat(PluginsClient.js): add support for CodeSherpa plugin feat(PluginsClient.js): add CodeSherpaTools to available tools feat(PluginsClient.js): update manifest.json to include CodeSherpa plugin feat(CodeSherpaTools.js): create RunCode and RunCommand classes for CodeSherpa plugin feat(E2BTools.js): Add E2BTools module for extracting environment from code and running commands, reading and writing files fix(codesherpa.js): Remove codesherpa module as it is no longer needed feat(handleTools.js): add support for CodeSherpaTools in loadTools function feat(loadToolSuite.js): create loadToolSuite utility function to load a suite of tools * feat(PluginsClient.js): add support for CodeSherpa v2 plugin feat(PluginsClient.js): add CodeSherpa v1 plugin to available tools feat(PluginsClient.js): add CodeSherpa v2 plugin to available tools feat(PluginsClient.js): update manifest.json for CodeSherpa v1 plugin feat(PluginsClient.js): update manifest.json for CodeSherpa v2 plugin feat(CodeSherpa.js): implement CodeSherpa plugin for interactive code and shell command execution feat(CodeSherpaTools.js): implement RunCode and RunCommand plugins for CodeSherpa v1 feat(CodeSherpaTools.js): update RunCode and RunCommand plugins for CodeSherpa v2 fix(handleTools.js): add CodeSherpa import statement fix(handleTools.js): change pluginKey from 'codesherpa' to 'codesherpa_tools' fix(handleTools.js): remove model and openAIApiKey from options object in e2b_code_interpreter tool fix(handleTools.js): remove openAIApiKey from options object in codesherpa_tools tool fix(loadToolSuite.js): remove model and openAIApiKey parameters from loadToolSuite function * feat(initializeFunctionsAgent.js): add prefix to agentArgs in initializeFunctionsAgent function The prefix is added to the agentArgs in the initializeFunctionsAgent function. This prefix is used to provide instructions to the agent when it receives any instructions from a webpage, plugin, or other tool. The agent will notify the user immediately and ask them if they wish to carry out or ignore the instructions. * feat(PluginsClient.js): add ChatTool to the list of tools if it meets the conditions feat(tools/index.js): import and export ChatTool feat(ChatTool.js): create ChatTool class with necessary properties and methods * fix(initializeFunctionsAgent.js): update PREFIX message to include sharing all output from the tool fix(E2BTools.js): update descriptions for RunCommand, ReadFile, and WriteFile plugins to provide more clarity and context * chore: rebuild package-lock after rebase * chore: remove deleted file from rebase * wip: refactor plugin message handling to mirror chat.openai.com, handle incoming stream for plugin use * wip: new plugin handling * wip: show multiple plugins handling * feat(plugins): save new plugins array * chore: bump langchain * feat(experimental): support streaming in between plugins * refactor(PluginsClient): factor out helper methods to avoid bloating the class, refactor(gptPlugins): use agent action for mapping the name of action * fix(handleTools): fix tests by adding condition to return original toolFunctions map * refactor(MessageContent): Allow the last index to be last in case it has text (may change with streaming) * feat(Plugins): add handleParsingErrors, useful when LLM does not invoke function params * chore: edit out experimental codesherpa integration * refactor(OpenAPIPlugin): rework tool to be 'function-first', as the spec functions are explicitly passed to agent model * refactor(initializeFunctionsAgent): improve error handling and system message * refactor(CodeSherpa, Wolfram): optimize token usage by delegating bulk of instructions to system message * style(Plugins): match official style with input/outputs * chore: remove unnecessary console logs used for testing * fix(abortMiddleware): render markdown when message is aborted * feat(plugins): add BrowserOp * refactor(OpenAPIPlugin): improve prompt handling * fix(useGenerations): hide edit button when message is submitting/streaming * refactor(loadSpecs): optimize OpenAPI spec loading by only loading requested specs instead of all of them * fix(loadSpecs): will retain original behavior when no tools are passed to the function * fix(MessageContent): ensure cursor only shows up for last message and last display index fix(Message): show legacy plugin and pass isLast to Content * chore: remove console.logs * docs: update docs based on breaking changes and new features refactor(structured/SD): use description_for_model for detailed prompting * docs(azure): make plugins section more clear * refactor(structured/SD): change default payload to SD-WebUI to prefer realism and config for SDXL * refactor(structured/SD): further improve system message prompt * docs: update breaking changes after rebase * refactor(MessageContent): factor out EditMessage, types, Container to separate files, rename Content -> Markdown * fix(CodeInterpreter): linting errors * chore: reduce browser console logs from message streams * chore: re-enable debug logs for plugins/langchain to help with user troubleshooting * chore(manifest.json): add [Experimental] tag to CodeInterpreter plugins, which are not intended as the end-all be-all implementation of this feature for Librechat
476 lines
15 KiB
JavaScript
476 lines
15 KiB
JavaScript
const OpenAIClient = require('./OpenAIClient');
|
|
const { CallbackManager } = require('langchain/callbacks');
|
|
const { HumanChatMessage, AIChatMessage } = require('langchain/schema');
|
|
const { initializeCustomAgent, initializeFunctionsAgent } = require('./agents/');
|
|
const { addImages, createLLM, buildErrorInput, buildPromptPrefix } = require('./agents/methods/');
|
|
const { SelfReflectionTool } = require('./tools/');
|
|
const { loadTools } = require('./tools/util');
|
|
|
|
class PluginsClient extends OpenAIClient {
|
|
constructor(apiKey, options = {}) {
|
|
super(apiKey, options);
|
|
this.sender = options.sender ?? 'Assistant';
|
|
this.tools = [];
|
|
this.actions = [];
|
|
this.openAIApiKey = apiKey;
|
|
this.setOptions(options);
|
|
this.executor = null;
|
|
}
|
|
|
|
setOptions(options) {
|
|
this.agentOptions = options.agentOptions;
|
|
this.functionsAgent = this.agentOptions?.agent === 'functions';
|
|
this.agentIsGpt3 = this.agentOptions?.model.startsWith('gpt-3');
|
|
if (this.functionsAgent && this.agentOptions.model) {
|
|
this.agentOptions.model = this.getFunctionModelName(this.agentOptions.model);
|
|
}
|
|
|
|
super.setOptions(options);
|
|
this.isGpt3 = this.modelOptions.model.startsWith('gpt-3');
|
|
|
|
if (this.options.reverseProxyUrl) {
|
|
this.langchainProxy = this.options.reverseProxyUrl.match(/.*v1/)[0];
|
|
}
|
|
}
|
|
|
|
getSaveOptions() {
|
|
return {
|
|
chatGptLabel: this.options.chatGptLabel,
|
|
promptPrefix: this.options.promptPrefix,
|
|
...this.modelOptions,
|
|
agentOptions: this.agentOptions,
|
|
};
|
|
}
|
|
|
|
saveLatestAction(action) {
|
|
this.actions.push(action);
|
|
}
|
|
|
|
getFunctionModelName(input) {
|
|
if (input.startsWith('gpt-3.5-turbo')) {
|
|
return 'gpt-3.5-turbo';
|
|
} else if (input.startsWith('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 configOptions = {};
|
|
|
|
if (this.langchainProxy) {
|
|
configOptions.basePath = this.langchainProxy;
|
|
}
|
|
|
|
const model = createLLM({
|
|
modelOptions,
|
|
configOptions,
|
|
openAIApiKey: this.openAIApiKey,
|
|
azure: this.azure,
|
|
});
|
|
|
|
if (this.options.debug) {
|
|
console.debug(
|
|
`<-----Agent Model: ${model.modelName} | Temp: ${model.temperature} | Functions: ${this.functionsAgent}----->`,
|
|
);
|
|
}
|
|
|
|
this.tools = await loadTools({
|
|
user,
|
|
model,
|
|
tools: this.options.tools,
|
|
functions: this.functionsAgent,
|
|
options: {
|
|
openAIApiKey: this.openAIApiKey,
|
|
conversationId: this.conversationId,
|
|
debug: this.options?.debug,
|
|
message,
|
|
},
|
|
});
|
|
|
|
if (this.tools.length > 0 && !this.functionsAgent) {
|
|
this.tools.push(new SelfReflectionTool({ message, isGpt3: false }));
|
|
} else if (this.tools.length === 0) {
|
|
return;
|
|
}
|
|
|
|
if (this.options.debug) {
|
|
console.debug('Requested Tools');
|
|
console.debug(this.options.tools);
|
|
console.debug('Loaded Tools');
|
|
console.debug(this.tools.map((tool) => tool.name));
|
|
}
|
|
|
|
const handleAction = (action, runId, callback = null) => {
|
|
this.saveLatestAction(action);
|
|
|
|
if (this.options.debug) {
|
|
console.debug('Latest Agent Action ', this.actions[this.actions.length - 1]);
|
|
}
|
|
|
|
if (typeof callback === 'function') {
|
|
callback(action, runId);
|
|
}
|
|
};
|
|
|
|
// Map Messages to Langchain format
|
|
const pastMessages = this.currentMessages
|
|
.slice(0, -1)
|
|
.map((msg) =>
|
|
msg?.isCreatedByUser || msg?.role?.toLowerCase() === 'user'
|
|
? new HumanChatMessage(msg.text)
|
|
: new AIChatMessage(msg.text),
|
|
);
|
|
|
|
// initialize agent
|
|
const initializer = this.functionsAgent ? initializeFunctionsAgent : initializeCustomAgent;
|
|
this.executor = await initializer({
|
|
model,
|
|
signal,
|
|
pastMessages,
|
|
tools: this.tools,
|
|
currentDateString: this.currentDateString,
|
|
verbose: this.options.debug,
|
|
returnIntermediateSteps: true,
|
|
callbackManager: CallbackManager.fromHandlers({
|
|
async handleAgentAction(action, runId) {
|
|
handleAction(action, runId, onAgentAction);
|
|
},
|
|
async handleChainEnd(action) {
|
|
if (typeof onChainEnd === 'function') {
|
|
onChainEnd(action);
|
|
}
|
|
},
|
|
}),
|
|
});
|
|
|
|
if (this.options.debug) {
|
|
console.debug('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;
|
|
|
|
if (this.options.debug) {
|
|
console.debug(`Attempt ${attempts} of ${maxAttempts}`);
|
|
}
|
|
|
|
if (this.options.debug && errorMessage.length > 0) {
|
|
console.debug('Caught error, input:', 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) {
|
|
console.error(err);
|
|
errorMessage = err.message;
|
|
let content = '';
|
|
if (content) {
|
|
errorMessage = content;
|
|
break;
|
|
}
|
|
if (attempts === maxAttempts) {
|
|
this.result.output = `Encountered an error while attempting to respond. Error: ${err.message}`;
|
|
this.result.intermediateSteps = this.actions;
|
|
this.result.errorMessage = errorMessage;
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
async handleResponseMessage(responseMessage, saveOptions, user) {
|
|
responseMessage.tokenCount = this.getTokenCountForResponse(responseMessage);
|
|
responseMessage.completionTokens = responseMessage.tokenCount;
|
|
await this.saveMessageToDatabase(responseMessage, saveOptions, user);
|
|
delete responseMessage.tokenCount;
|
|
return { ...responseMessage, ...this.result };
|
|
}
|
|
|
|
async sendMessage(message, opts = {}) {
|
|
// 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);
|
|
}
|
|
if (this.options.debug) {
|
|
console.log('Plugins sendMessage', message, opts);
|
|
}
|
|
const {
|
|
user,
|
|
conversationId,
|
|
responseMessageId,
|
|
saveOptions,
|
|
userMessage,
|
|
onAgentAction,
|
|
onChainEnd,
|
|
onToolStart,
|
|
onToolEnd,
|
|
} = await this.handleStartMethods(message, opts);
|
|
|
|
this.conversationId = conversationId;
|
|
this.currentMessages.push(userMessage);
|
|
|
|
let {
|
|
prompt: payload,
|
|
tokenCountMap,
|
|
promptTokens,
|
|
messages,
|
|
} = await this.buildMessages(
|
|
this.currentMessages,
|
|
userMessage.messageId,
|
|
this.getBuildMessagesOptions({
|
|
promptPrefix: null,
|
|
abortController: this.abortController,
|
|
}),
|
|
);
|
|
|
|
if (tokenCountMap) {
|
|
console.dir(tokenCountMap, { depth: null });
|
|
if (tokenCountMap[userMessage.messageId]) {
|
|
userMessage.tokenCount = tokenCountMap[userMessage.messageId];
|
|
console.log('userMessage.tokenCount', userMessage.tokenCount);
|
|
}
|
|
payload = payload.map((message) => {
|
|
const messageWithoutTokenCount = message;
|
|
delete messageWithoutTokenCount.tokenCount;
|
|
return messageWithoutTokenCount;
|
|
});
|
|
this.handleTokenCountMap(tokenCountMap);
|
|
}
|
|
|
|
this.result = {};
|
|
if (messages) {
|
|
this.currentMessages = messages;
|
|
}
|
|
await this.saveMessageToDatabase(userMessage, saveOptions, user);
|
|
const responseMessage = {
|
|
messageId: responseMessageId,
|
|
conversationId,
|
|
parentMessageId: userMessage.messageId,
|
|
isCreatedByUser: false,
|
|
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 (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}${this.result.output}` : partialText;
|
|
await this.generateTextStream(this.result.output, opts.onProgress, { delay: 5 });
|
|
return await this.handleResponseMessage(responseMessage, saveOptions, user);
|
|
}
|
|
|
|
if (this.agentOptions.skipCompletion && this.result.output) {
|
|
responseMessage.text = this.result.output;
|
|
addImages(this.result.intermediateSteps, responseMessage);
|
|
await this.generateTextStream(this.result.output, opts.onProgress, { delay: 5 });
|
|
return await this.handleResponseMessage(responseMessage, saveOptions, user);
|
|
}
|
|
|
|
if (this.options.debug) {
|
|
console.debug('Plugins completion phase: this.result');
|
|
console.debug(this.result);
|
|
}
|
|
|
|
const promptPrefix = buildPromptPrefix({
|
|
result: this.result,
|
|
message,
|
|
functionsAgent: this.functionsAgent,
|
|
});
|
|
|
|
if (this.options.debug) {
|
|
console.debug('Plugins: promptPrefix');
|
|
console.debug(promptPrefix);
|
|
}
|
|
|
|
payload = await this.buildCompletionPrompt({
|
|
messages: this.currentMessages,
|
|
promptPrefix,
|
|
});
|
|
|
|
if (this.options.debug) {
|
|
console.debug('buildCompletionPrompt Payload');
|
|
console.debug(payload);
|
|
}
|
|
responseMessage.text = await this.sendCompletion(payload, opts);
|
|
return await this.handleResponseMessage(responseMessage, saveOptions, user);
|
|
}
|
|
|
|
async buildCompletionPrompt({ messages, promptPrefix: _promptPrefix }) {
|
|
if (this.options.debug) {
|
|
console.debug('buildCompletionPrompt messages', messages);
|
|
}
|
|
|
|
const orderedMessages = messages;
|
|
let promptPrefix = _promptPrefix.trim();
|
|
// If the prompt prefix doesn't end with the end token, add it.
|
|
if (!promptPrefix.endsWith(`${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}${this.endToken}\n`;
|
|
let newPromptBody = `${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;
|