LibreChat/api/app/clients/prompts/formatMessages.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

260 lines
9.3 KiB
JavaScript

const { ToolMessage } = require('@langchain/core/messages');
const { EModelEndpoint, ContentTypes } = require('librechat-data-provider');
const { HumanMessage, AIMessage, SystemMessage } = require('@langchain/core/messages');
/**
* Formats a message to OpenAI Vision API payload format.
*
* @param {Object} params - The parameters for formatting.
* @param {Object} params.message - The message object to format.
* @param {string} [params.message.role] - The role of the message sender (must be 'user').
* @param {string} [params.message.content] - The text content of the message.
* @param {EModelEndpoint} [params.endpoint] - Identifier for specific endpoint handling
* @param {Array<string>} [params.image_urls] - The image_urls to attach to the message.
* @returns {(Object)} - The formatted message.
*/
const formatVisionMessage = ({ message, image_urls, endpoint }) => {
if (endpoint === EModelEndpoint.anthropic) {
message.content = [...image_urls, { type: ContentTypes.TEXT, text: message.content }];
return message;
}
message.content = [{ type: ContentTypes.TEXT, text: message.content }, ...image_urls];
return message;
};
/**
* Formats a message to OpenAI payload format based on the provided options.
*
* @param {Object} params - The parameters for formatting.
* @param {Object} params.message - The message object to format.
* @param {string} [params.message.role] - The role of the message sender (e.g., 'user', 'assistant').
* @param {string} [params.message._name] - The name associated with the message.
* @param {string} [params.message.sender] - The sender of the message.
* @param {string} [params.message.text] - The text content of the message.
* @param {string} [params.message.content] - The content of the message.
* @param {Array<string>} [params.message.image_urls] - The image_urls attached to the message for Vision API.
* @param {string} [params.userName] - The name of the user.
* @param {string} [params.assistantName] - The name of the assistant.
* @param {string} [params.endpoint] - Identifier for specific endpoint handling
* @param {boolean} [params.langChain=false] - Whether to return a LangChain message object.
* @returns {(Object|HumanMessage|AIMessage|SystemMessage)} - The formatted message.
*/
const formatMessage = ({ message, userName, assistantName, endpoint, langChain = false }) => {
let { role: _role, _name, sender, text, content: _content, lc_id } = message;
if (lc_id && lc_id[2] && !langChain) {
const roleMapping = {
SystemMessage: 'system',
HumanMessage: 'user',
AIMessage: 'assistant',
};
_role = roleMapping[lc_id[2]];
}
const role = _role ?? (sender && sender?.toLowerCase() === 'user' ? 'user' : 'assistant');
const content = _content ?? text ?? '';
const formattedMessage = {
role,
content,
};
const { image_urls } = message;
if (Array.isArray(image_urls) && image_urls.length > 0 && role === 'user') {
return formatVisionMessage({
message: formattedMessage,
image_urls: message.image_urls,
endpoint,
});
}
if (_name) {
formattedMessage.name = _name;
}
if (userName && formattedMessage.role === 'user') {
formattedMessage.name = userName;
}
if (assistantName && formattedMessage.role === 'assistant') {
formattedMessage.name = assistantName;
}
if (formattedMessage.name) {
// Conform to API regex: ^[a-zA-Z0-9_-]{1,64}$
// https://community.openai.com/t/the-format-of-the-name-field-in-the-documentation-is-incorrect/175684/2
formattedMessage.name = formattedMessage.name.replace(/[^a-zA-Z0-9_-]/g, '_');
if (formattedMessage.name.length > 64) {
formattedMessage.name = formattedMessage.name.substring(0, 64);
}
}
if (!langChain) {
return formattedMessage;
}
if (role === 'user') {
return new HumanMessage(formattedMessage);
} else if (role === 'assistant') {
return new AIMessage(formattedMessage);
} else {
return new SystemMessage(formattedMessage);
}
};
/**
* Formats an array of messages for LangChain.
*
* @param {Array<Object>} messages - The array of messages to format.
* @param {Object} formatOptions - The options for formatting each message.
* @param {string} [formatOptions.userName] - The name of the user.
* @param {string} [formatOptions.assistantName] - The name of the assistant.
* @returns {Array<(HumanMessage|AIMessage|SystemMessage)>} - The array of formatted LangChain messages.
*/
const formatLangChainMessages = (messages, formatOptions) =>
messages.map((msg) => formatMessage({ ...formatOptions, message: msg, langChain: true }));
/**
* Formats a LangChain message object by merging properties from `lc_kwargs` or `kwargs` and `additional_kwargs`.
*
* @param {Object} message - The message object to format.
* @param {Object} [message.lc_kwargs] - Contains properties to be merged. Either this or `message.kwargs` should be provided.
* @param {Object} [message.kwargs] - Contains properties to be merged. Either this or `message.lc_kwargs` should be provided.
* @param {Object} [message.kwargs.additional_kwargs] - Additional properties to be merged.
*
* @returns {Object} The formatted LangChain message.
*/
const formatFromLangChain = (message) => {
const { additional_kwargs, ...message_kwargs } = message.lc_kwargs ?? message.kwargs;
return {
...message_kwargs,
...additional_kwargs,
};
};
/**
* Formats an array of messages for LangChain, handling tool calls and creating ToolMessage instances.
*
* @param {Array<Partial<TMessage>>} payload - The array of messages to format.
* @returns {Array<(HumanMessage|AIMessage|SystemMessage|ToolMessage)>} - The array of formatted LangChain messages, including ToolMessages for tool calls.
*/
const formatAgentMessages = (payload) => {
const messages = [];
for (const message of payload) {
if (typeof message.content === 'string') {
message.content = [{ type: ContentTypes.TEXT, [ContentTypes.TEXT]: message.content }];
}
if (message.role !== 'assistant') {
messages.push(formatMessage({ message, langChain: true }));
continue;
}
let currentContent = [];
let lastAIMessage = null;
for (const part of message.content) {
if (part.type === ContentTypes.TEXT && part.tool_call_ids) {
/*
If there's pending content, it needs to be aggregated as a single string to prepare for tool calls.
For Anthropic models, the "tool_calls" field on a message is only respected if content is a string.
*/
if (currentContent.length > 0) {
let content = currentContent.reduce((acc, curr) => {
if (curr.type === ContentTypes.TEXT) {
return `${acc}${curr[ContentTypes.TEXT]}\n`;
}
return acc;
}, '');
content = `${content}\n${part[ContentTypes.TEXT] ?? ''}`.trim();
lastAIMessage = new AIMessage({ content });
messages.push(lastAIMessage);
currentContent = [];
continue;
}
// Create a new AIMessage with this text and prepare for tool calls
lastAIMessage = new AIMessage({
content: part.text || '',
});
messages.push(lastAIMessage);
} else if (part.type === ContentTypes.TOOL_CALL) {
if (!lastAIMessage) {
throw new Error('Invalid tool call structure: No preceding AIMessage with tool_call_ids');
}
// Note: `tool_calls` list is defined when constructed by `AIMessage` class, and outputs should be excluded from it
const { output, args: _args, ...tool_call } = part.tool_call;
// TODO: investigate; args as dictionary may need to be provider-or-tool-specific
let args = _args;
try {
args = JSON.parse(_args);
} catch (e) {
if (typeof _args === 'string') {
args = { input: _args };
}
}
tool_call.args = args;
lastAIMessage.tool_calls.push(tool_call);
// Add the corresponding ToolMessage
messages.push(
new ToolMessage({
tool_call_id: tool_call.id,
name: tool_call.name,
content: output || '',
}),
);
} else {
currentContent.push(part);
}
}
if (currentContent.length > 0) {
messages.push(new AIMessage({ content: currentContent }));
}
}
return messages;
};
/**
* Formats an array of messages for LangChain, making sure all content fields are strings
* @param {Array<(HumanMessage|AIMessage|SystemMessage|ToolMessage)>} payload - The array of messages to format.
* @returns {Array<(HumanMessage|AIMessage|SystemMessage|ToolMessage)>} - The array of formatted LangChain messages, including ToolMessages for tool calls.
*/
const formatContentStrings = (payload) => {
const messages = [];
for (const message of payload) {
if (typeof message.content === 'string') {
continue;
}
if (!Array.isArray(message.content)) {
continue;
}
// Reduce text types to a single string, ignore all other types
const content = message.content.reduce((acc, curr) => {
if (curr.type === ContentTypes.TEXT) {
return `${acc}${curr[ContentTypes.TEXT]}\n`;
}
return acc;
}, '');
message.content = content.trim();
}
return messages;
};
module.exports = {
formatMessage,
formatFromLangChain,
formatAgentMessages,
formatContentStrings,
formatLangChainMessages,
};