mirror of
https://github.com/danny-avila/LibreChat.git
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* feat: Add BedrockIcon component to SVG library * feat: EModelEndpoint.bedrock * feat: first pass, bedrock chat. note: AgentClient is returning `agents` as conversation.endpoint * fix: declare endpoint in initialization step * chore: Update @librechat/agents dependency to version 1.4.5 * feat: backend content aggregation for agents/bedrock * feat: abort agent requests * feat: AWS Bedrock icons * WIP: agent provider schema parsing * chore: Update EditIcon props type * refactor(useGenerationsByLatest): make agents and bedrock editable * refactor: non-assistant message content, parts * fix: Bedrock response `sender` * fix: use endpointOption.model_parameters not endpointOption.modelOptions * fix: types for step handler * refactor: Update Agents.ToolCallDelta type * refactor: Remove unnecessary assignment of parentMessageId in AskController * refactor: remove unnecessary assignment of parentMessageId (agent request handler) * fix(bedrock/agents): message regeneration * refactor: dynamic form elements using react-hook-form Controllers * fix: agent icons/labels for messages * fix: agent actions * fix: use of new dynamic tags causing application crash * refactor: dynamic settings touch-ups * refactor: update Slider component to allow custom track class name * refactor: update DynamicSlider component styles * refactor: use Constants value for GLOBAL_PROJECT_NAME (enum) * feat: agent share global methods/controllers * fix: agents query * fix: `getResponseModel` * fix: share prompt a11y issue * refactor: update SharePrompt dialog theme styles * refactor: explicit typing for SharePrompt * feat: add agent roles/permissions * chore: update @librechat/agents dependency to version 1.4.7 for tool_call_ids edge case * fix(Anthropic): messages.X.content.Y.tool_use.input: Input should be a valid dictionary * fix: handle text parts with tool_call_ids and empty text * fix: role initialization * refactor: don't make instructions required * refactor: improve typing of Text part * fix: setShowStopButton for agents route * chore: remove params for now * fix: add streamBuffer and streamRate to help prevent 'Overloaded' errors from Anthropic API * refactor: remove console.log statement in ContentRender component * chore: typing, rename Context to Delete Button * chore(DeleteButton): logging * refactor(Action): make accessible * style(Action): improve a11y again * refactor: remove use/mention of mongoose sessions * feat: first pass, sharing agents * feat: visual indicator for global agent, remove author when serving to non-author * wip: params * chore: fix typing issues * fix(schemas): typing * refactor: improve accessibility of ListCard component and fix console React warning * wip: reset templates for non-legacy new convos * Revert "wip: params" This reverts commitf8067e91d4. * Revert "refactor: dynamic form elements using react-hook-form Controllers" This reverts commit2150c4815d. * fix(Parameters): types and parameter effect update to only update local state to parameters * refactor: optimize useDebouncedInput hook for better performance * feat: first pass, anthropic bedrock params * chore: paramEndpoints check for endpointType too * fix: maxTokens to use coerceNumber.optional(), * feat: extra chat model params * chore: reduce code repetition * refactor: improve preset title handling in SaveAsPresetDialog component * refactor: improve preset handling in HeaderOptions component * chore: improve typing, replace legacy dialog for SaveAsPresetDialog * feat: save as preset from parameters panel * fix: multi-search in select dropdown when using Option type * refactor: update default showDefault value to false in Dynamic components * feat: Bedrock presets settings * chore: config, fix agents schema, update config version * refactor: update AWS region variable name in bedrock options endpoint to BEDROCK_AWS_DEFAULT_REGION * refactor: update baseEndpointSchema in config.ts to include baseURL property * refactor: update createRun function to include req parameter and set streamRate based on provider * feat: availableRegions via config * refactor: remove unused demo agent controller file * WIP: title * Update @librechat/agents to version 1.5.0 * chore: addTitle.js to handle empty responseText * feat: support images and titles * feat: context token updates * Refactor BaseClient test to use expect.objectContaining * refactor: add model select, remove header options params, move side panel params below prompts * chore: update models list, catch title error * feat: model service for bedrock models (env) * chore: Remove verbose debug log in AgentClient class following stream * feat(bedrock): track token spend; fix: token rates, value key mapping for AWS models * refactor: handle streamRate in `handleLLMNewToken` callback * chore: AWS Bedrock example config in `.env.example` * refactor: Rename bedrockMeta to bedrockGeneral in settings.ts and use for AI21 and Amazon Bedrock providers * refactor: Update `.env.example` with AWS Bedrock model IDs URL and additional notes * feat: titleModel support for bedrock * refactor: Update `.env.example` with additional notes for AWS Bedrock model IDs
210 lines
7.7 KiB
JavaScript
210 lines
7.7 KiB
JavaScript
const { ToolMessage } = require('@langchain/core/messages');
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const { EModelEndpoint, ContentTypes } = require('librechat-data-provider');
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const { HumanMessage, AIMessage, SystemMessage } = require('langchain/schema');
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/**
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* Formats a message to OpenAI Vision API payload format.
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*
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* @param {Object} params - The parameters for formatting.
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* @param {Object} params.message - The message object to format.
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* @param {string} [params.message.role] - The role of the message sender (must be 'user').
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* @param {string} [params.message.content] - The text content of the message.
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* @param {EModelEndpoint} [params.endpoint] - Identifier for specific endpoint handling
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* @param {Array<string>} [params.image_urls] - The image_urls to attach to the message.
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* @returns {(Object)} - The formatted message.
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*/
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const formatVisionMessage = ({ message, image_urls, endpoint }) => {
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if (endpoint === EModelEndpoint.anthropic) {
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message.content = [...image_urls, { type: ContentTypes.TEXT, text: message.content }];
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return message;
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}
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message.content = [{ type: ContentTypes.TEXT, text: message.content }, ...image_urls];
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return message;
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};
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/**
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* Formats a message to OpenAI payload format based on the provided options.
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*
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* @param {Object} params - The parameters for formatting.
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* @param {Object} params.message - The message object to format.
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* @param {string} [params.message.role] - The role of the message sender (e.g., 'user', 'assistant').
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* @param {string} [params.message._name] - The name associated with the message.
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* @param {string} [params.message.sender] - The sender of the message.
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* @param {string} [params.message.text] - The text content of the message.
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* @param {string} [params.message.content] - The content of the message.
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* @param {Array<string>} [params.message.image_urls] - The image_urls attached to the message for Vision API.
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* @param {string} [params.userName] - The name of the user.
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* @param {string} [params.assistantName] - The name of the assistant.
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* @param {string} [params.endpoint] - Identifier for specific endpoint handling
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* @param {boolean} [params.langChain=false] - Whether to return a LangChain message object.
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* @returns {(Object|HumanMessage|AIMessage|SystemMessage)} - The formatted message.
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*/
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const formatMessage = ({ message, userName, assistantName, endpoint, langChain = false }) => {
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let { role: _role, _name, sender, text, content: _content, lc_id } = message;
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if (lc_id && lc_id[2] && !langChain) {
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const roleMapping = {
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SystemMessage: 'system',
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HumanMessage: 'user',
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AIMessage: 'assistant',
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};
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_role = roleMapping[lc_id[2]];
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}
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const role = _role ?? (sender && sender?.toLowerCase() === 'user' ? 'user' : 'assistant');
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const content = _content ?? text ?? '';
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const formattedMessage = {
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role,
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content,
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};
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const { image_urls } = message;
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if (Array.isArray(image_urls) && image_urls.length > 0 && role === 'user') {
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return formatVisionMessage({
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message: formattedMessage,
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image_urls: message.image_urls,
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endpoint,
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});
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}
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if (_name) {
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formattedMessage.name = _name;
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}
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if (userName && formattedMessage.role === 'user') {
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formattedMessage.name = userName;
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}
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if (assistantName && formattedMessage.role === 'assistant') {
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formattedMessage.name = assistantName;
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}
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if (formattedMessage.name) {
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// Conform to API regex: ^[a-zA-Z0-9_-]{1,64}$
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// https://community.openai.com/t/the-format-of-the-name-field-in-the-documentation-is-incorrect/175684/2
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formattedMessage.name = formattedMessage.name.replace(/[^a-zA-Z0-9_-]/g, '_');
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if (formattedMessage.name.length > 64) {
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formattedMessage.name = formattedMessage.name.substring(0, 64);
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}
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}
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if (!langChain) {
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return formattedMessage;
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}
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if (role === 'user') {
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return new HumanMessage(formattedMessage);
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} else if (role === 'assistant') {
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return new AIMessage(formattedMessage);
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} else {
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return new SystemMessage(formattedMessage);
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}
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};
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/**
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* Formats an array of messages for LangChain.
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*
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* @param {Array<Object>} messages - The array of messages to format.
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* @param {Object} formatOptions - The options for formatting each message.
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* @param {string} [formatOptions.userName] - The name of the user.
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* @param {string} [formatOptions.assistantName] - The name of the assistant.
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* @returns {Array<(HumanMessage|AIMessage|SystemMessage)>} - The array of formatted LangChain messages.
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*/
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const formatLangChainMessages = (messages, formatOptions) =>
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messages.map((msg) => formatMessage({ ...formatOptions, message: msg, langChain: true }));
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/**
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* Formats a LangChain message object by merging properties from `lc_kwargs` or `kwargs` and `additional_kwargs`.
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*
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* @param {Object} message - The message object to format.
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* @param {Object} [message.lc_kwargs] - Contains properties to be merged. Either this or `message.kwargs` should be provided.
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* @param {Object} [message.kwargs] - Contains properties to be merged. Either this or `message.lc_kwargs` should be provided.
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* @param {Object} [message.kwargs.additional_kwargs] - Additional properties to be merged.
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*
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* @returns {Object} The formatted LangChain message.
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*/
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const formatFromLangChain = (message) => {
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const { additional_kwargs, ...message_kwargs } = message.lc_kwargs ?? message.kwargs;
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return {
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...message_kwargs,
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...additional_kwargs,
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};
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};
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/**
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* Formats an array of messages for LangChain, handling tool calls and creating ToolMessage instances.
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*
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* @param {Array<Partial<TMessage>>} payload - The array of messages to format.
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* @returns {Array<(HumanMessage|AIMessage|SystemMessage|ToolMessage)>} - The array of formatted LangChain messages, including ToolMessages for tool calls.
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*/
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const formatAgentMessages = (payload) => {
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const messages = [];
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for (const message of payload) {
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if (message.role !== 'assistant') {
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messages.push(formatMessage({ message, langChain: true }));
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continue;
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}
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let currentContent = [];
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let lastAIMessage = null;
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for (const part of message.content) {
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if (part.type === ContentTypes.TEXT && part.tool_call_ids) {
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// If there's pending content, add it as an AIMessage
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if (currentContent.length > 0) {
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messages.push(new AIMessage({ content: currentContent }));
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currentContent = [];
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}
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// Create a new AIMessage with this text and prepare for tool calls
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lastAIMessage = new AIMessage({
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content: part.text || '',
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});
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messages.push(lastAIMessage);
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} else if (part.type === ContentTypes.TOOL_CALL) {
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if (!lastAIMessage) {
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throw new Error('Invalid tool call structure: No preceding AIMessage with tool_call_ids');
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}
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// Note: `tool_calls` list is defined when constructed by `AIMessage` class, and outputs should be excluded from it
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const { output, args: _args, ...tool_call } = part.tool_call;
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// TODO: investigate; args as dictionary may need to be provider-or-tool-specific
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let args = _args;
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try {
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args = JSON.parse(args);
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} catch (e) {
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// failed to parse, leave as is
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}
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tool_call.args = args;
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lastAIMessage.tool_calls.push(tool_call);
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// Add the corresponding ToolMessage
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messages.push(
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new ToolMessage({
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tool_call_id: tool_call.id,
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name: tool_call.name,
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content: output,
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}),
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);
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} else {
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currentContent.push(part);
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}
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}
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if (currentContent.length > 0) {
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messages.push(new AIMessage({ content: currentContent }));
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}
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}
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return messages;
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};
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module.exports = {
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formatMessage,
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formatFromLangChain,
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formatAgentMessages,
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formatLangChainMessages,
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};
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